predict.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<ul>\n",
    "    <h3><b>CLIENTE: Felipe Prazeres</b></h3>\n",
    "    <ul>\n",
    "            <li> <b>Rlatorio de Performance e Gerenciamento de Carteira</b> </li>\n",
    "            <li> <b>02/03/2021</b> </li>\n",
    "            <li> <b>Serie temporal de 3 meses</b> </li>\n",
    "    </ul>\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "<ul>\n",
    "<li>Fonte: http://www.bmfbovespa.com.br/pt_br/produtos/indices/</li>\n",
    "<li>yahoo finance API</li>\n",
    "</ul>    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_names = ['OIBR3.SA',\n",
    " 'VVAR3.SA',\n",
    " 'PETR4.SA',\n",
    " 'COGN3.SA',\n",
    " 'MGLU3.SA',\n",
    " 'BBDC4.SA',\n",
    " 'ITUB4.SA',\n",
    " 'IRBR3.SA',\n",
    " 'CIEL3.SA',\n",
    " 'ITSA4.SA',\n",
    " 'VALE3.SA',\n",
    " 'ABEV3.SA',\n",
    " 'USIM5.SA',\n",
    " 'PETR3.SA',\n",
    " 'BBAS3.SA',\n",
    " 'JBSS3.SA',\n",
    " 'BRML3.SA',\n",
    " 'GGBR4.SA',\n",
    " 'GOAU4.SA',\n",
    " 'CSNA3.SA',\n",
    " 'EMBR3.SA',\n",
    " 'B3SA3.SA',\n",
    " 'AZUL4.SA',\n",
    " 'MRFG3.SA',\n",
    " 'CMIG4.SA',\n",
    " 'NGRD3.SA',\n",
    " 'GOLL4.SA',\n",
    " 'MEAL3.SA',\n",
    " 'HAPV3.SA',\n",
    " 'RAIL3.SA',\n",
    " 'BRFS3.SA',\n",
    " 'LAME4.SA',\n",
    " 'CCRO3.SA',\n",
    " 'JHSF3.SA',\n",
    " 'POMO4.SA',\n",
    " 'EQTL3.SA',\n",
    " 'LREN3.SA',\n",
    " 'SUZB3.SA',\n",
    " 'BEEF3.SA',\n",
    " 'BRDT3.SA',\n",
    " 'CYRE3.SA',\n",
    " 'UGPA3.SA',\n",
    " 'RADL3.SA',\n",
    " 'NTCO3.SA',\n",
    " 'ENEV3.SA',\n",
    " 'MULT3.SA',\n",
    " 'CVCB3.SA',\n",
    " 'RENT3.SA',\n",
    " 'DMMO3.SA',\n",
    " 'WEGE3.SA',\n",
    " 'KLBN11.SA',\n",
    " 'BBDC3.SA',\n",
    " 'ELET3.SA',\n",
    " 'TOTS3.SA',\n",
    " 'LWSA3.SA',\n",
    " 'GFSA3.SA',\n",
    " 'OIBR4.SA',\n",
    " 'AERI3.SA',\n",
    " 'AMAR3.SA',\n",
    " 'CRFB3.SA',\n",
    " 'MRVE3.SA',\n",
    " 'BBSE3.SA',\n",
    " 'PRIO3.SA',\n",
    " 'STBP3.SA',\n",
    " 'ECOR3.SA',\n",
    " 'BTOW3.SA',\n",
    " 'SBSP3.SA',\n",
    " 'YDUQ3.SA',\n",
    " 'QUAL3.SA',\n",
    " 'GNDI3.SA',\n",
    " 'RCSL4.SA',\n",
    " 'RAPT4.SA',\n",
    " 'GMAT3.SA',\n",
    " 'HYPE3.SA',\n",
    " 'BPAN4.SA',\n",
    " 'PETZ3.SA',\n",
    " 'BPAC11.SA',\n",
    " 'BRKM5.SA',\n",
    " 'LCAM3.SA',\n",
    " 'DTEX3.SA',\n",
    " 'LIGT3.SA',\n",
    " 'SAPR4.SA',\n",
    " 'HGTX3.SA',\n",
    " 'ELET6.SA',\n",
    " 'ENBR3.SA',\n",
    " 'CPFE3.SA',\n",
    " 'SANB11.SA',\n",
    " 'MOVI3.SA',\n",
    " 'EZTC3.SA',\n",
    " 'NEOE3.SA',\n",
    " 'POSI3.SA',\n",
    " 'CSMG3.SA',\n",
    " 'HBSA3.SA',\n",
    " 'BRPR3.SA',\n",
    " 'BRAP4.SA',\n",
    " 'HBOR3.SA',\n",
    " 'CEAB3.SA',\n",
    " 'PTBL3.SA',\n",
    " 'TAEE11.SA',\n",
    " 'BRSR6.SA',\n",
    " 'IGTA3.SA',\n",
    " 'BIDI4.SA',\n",
    " 'FLRY3.SA',\n",
    " 'EVEN3.SA',\n",
    " 'MYPK3.SA',\n",
    " 'CESP6.SA',\n",
    " 'CASH3.SA',\n",
    " 'CSAN3.SA',\n",
    " 'KLBN4.SA',\n",
    " 'LAME3.SA',\n",
    " 'CNTO3.SA',\n",
    " 'LINX3.SA',\n",
    " 'TASA4.SA',\n",
    " 'SAPR11.SA',\n",
    " 'BKBR3.SA',\n",
    " 'ENJU3.SA',\n",
    " 'ENAT3.SA',\n",
    " 'ALPA4.SA',\n",
    " 'TRIS3.SA',\n",
    " 'EGIE3.SA',\n",
    " 'SMLS3.SA',\n",
    " 'TRPL4.SA',\n",
    " 'ODPV3.SA',\n",
    " 'ALSO3.SA',\n",
    " 'TCSA3.SA',\n",
    " 'RANI3.SA',\n",
    " 'MILS3.SA',\n",
    " 'PCAR3.SA',\n",
    " 'CAML3.SA',\n",
    " 'GRND3.SA',\n",
    " 'LJQQ3.SA',\n",
    " 'CMIG3.SA',\n",
    " 'BMGB4.SA',\n",
    " 'TIET11.SA',\n",
    " 'SOMA3.SA',\n",
    " 'SMTO3.SA',\n",
    " 'ENGI11.SA',\n",
    " 'DIRR3.SA',\n",
    " 'VIVA3.SA',\n",
    " 'CPLE6.SA',\n",
    " 'ETER3.SA',\n",
    " 'TEND3.SA',\n",
    " 'SLCE3.SA',\n",
    " 'GUAR3.SA',\n",
    " 'MDIA3.SA',\n",
    " 'LAVV3.SA',\n",
    " 'LOGN3.SA',\n",
    " 'SEER3.SA',\n",
    " 'TUPY3.SA',\n",
    " 'LPSB3.SA',\n",
    " 'PSSA3.SA',\n",
    " 'VULC3.SA',\n",
    " 'WIZS3.SA',\n",
    " 'SLED4.SA',\n",
    " 'ABCB4.SA',\n",
    " 'VLID3.SA',\n",
    " 'OMGE3.SA',\n",
    " 'RLOG3.SA',\n",
    " 'BIDI11.SA',\n",
    " 'ITUB3.SA',\n",
    " 'SQIA3.SA',\n",
    " 'BOAS3.SA',\n",
    " 'TIET4.SA',\n",
    " 'ALUP11.SA',\n",
    " 'TPIS3.SA',\n",
    " 'ANIM3.SA',\n",
    " 'PFRM3.SA',\n",
    " 'TECN3.SA',\n",
    " 'SHOW3.SA',\n",
    " 'ARZZ3.SA',\n",
    " 'VIVR3.SA',\n",
    " 'PGMN3.SA',\n",
    " 'SEQL3.SA',\n",
    " 'TGMA3.SA',\n",
    " 'AALR3.SA',\n",
    " 'MTRE3.SA',\n",
    " 'MELK3.SA',\n",
    " 'PARD3.SA',\n",
    " 'SIMH3.SA',\n",
    " 'BBRK3.SA',\n",
    " 'PNVL3.SA',\n",
    " 'LOGG3.SA',\n",
    " 'ROMI3.SA',\n",
    " 'PLPL3.SA',\n",
    " 'MDNE3.SA',\n",
    " 'LEVE3.SA',\n",
    " 'LUPA3.SA',\n",
    " 'KLBN3.SA',\n",
    " 'CCPR3.SA',\n",
    " 'BIDI3.SA',\n",
    " 'RRRP3.SA',\n",
    " 'JSLG3.SA',\n",
    " 'CPLE3.SA',\n",
    " 'AMBP3.SA',\n",
    " 'PINE4.SA',\n",
    " 'SAPR3.SA',\n",
    " 'DMVF3.SA',\n",
    " 'POMO3.SA',\n",
    " 'USIM3.SA',\n",
    " 'JPSA3.SA',\n",
    " 'FESA4.SA',\n",
    " 'SHUL4.SA',\n",
    " 'ITSA3.SA',\n",
    " 'CARD3.SA',\n",
    " 'UNIP6.SA',\n",
    " 'TIET3.SA',\n",
    " 'SLED3.SA',\n",
    " 'AGRO3.SA',\n",
    " 'PRNR3.SA',\n",
    " 'LLIS3.SA',\n",
    " 'SGPS3.SA',\n",
    " 'FHER3.SA',\n",
    " 'SANB4.SA',\n",
    " 'PMAM3.SA',\n",
    " 'TASA3.SA',\n",
    " 'RSID3.SA',\n",
    " 'SANB3.SA',\n",
    " 'FRAS3.SA',\n",
    " 'TAEE4.SA',\n",
    " 'GGBR3.SA',\n",
    " 'UCAS3.SA',\n",
    " 'KEPL3.SA',\n",
    " 'GPCP3.SA',\n",
    " 'VIVT3.SA',\n",
    " 'CAMB3.SA',\n",
    " 'BSEV3.SA',\n",
    " 'BOBR4.SA',\n",
    " 'ATOM3.SA',\n",
    " 'GOAU3.SA',\n",
    " 'IGBR3.SA',\n",
    " 'EUCA4.SA',\n",
    " 'RCSL3.SA',\n",
    " 'TAEE3.SA',\n",
    " 'PDGR3.SA',\n",
    " 'RPMG3.SA',\n",
    " 'ALPK3.SA',\n",
    " 'TCNO4.SA',\n",
    " 'HAGA4.SA',\n",
    " 'JBDU4.SA',\n",
    " 'AZEV4.SA',\n",
    " 'EALT4.SA',\n",
    " 'TESA3.SA',\n",
    " 'RNEW4.SA',\n",
    " 'BEES3.SA',\n",
    " 'WHRL4.SA',\n",
    " 'APER3.SA',\n",
    " 'RDNI3.SA',\n",
    " 'EQPA3.SA',\n",
    " 'MMXM3.SA',\n",
    " 'BIOM3.SA',\n",
    " 'BRAP3.SA',\n",
    " 'ENGI4.SA',\n",
    " 'TCNO3.SA',\n",
    " 'PTNT4.SA',\n",
    " 'ALUP4.SA',\n",
    " 'CTNM4.SA',\n",
    " 'COCE5.SA',\n",
    " 'RNEW3.SA',\n",
    " 'BRKM3.SA',\n",
    " 'ADHM3.SA',\n",
    " 'PNVL4.SA',\n",
    " 'OFSA3.SA',\n",
    " 'TELB4.SA',\n",
    " 'ALUP3.SA',\n",
    " 'RAPT3.SA',\n",
    " 'SNSY5.SA',\n",
    " 'CGRA4.SA',\n",
    " 'CRPG5.SA',\n",
    " 'SULA4.SA',\n",
    " 'ATMP3.SA',\n",
    " 'INEP4.SA',\n",
    " 'ENGI3.SA',\n",
    " 'BRSR3.SA',\n",
    " 'MWET4.SA',\n",
    " 'TXRX4.SA',\n",
    " 'FRTA3.SA',\n",
    " 'WHRL3.SA',\n",
    " 'SCAR3.SA',\n",
    " 'JBDU3.SA',\n",
    " 'OSXB3.SA',\n",
    " 'CESP3.SA',\n",
    " 'HAGA3.SA',\n",
    " 'CTSA4.SA',\n",
    " 'INEP3.SA',\n",
    " 'BMEB4.SA',\n",
    " 'AZEV3.SA',\n",
    " 'MNPR3.SA',\n",
    " 'CTSA3.SA',\n",
    " 'CLSC4.SA',\n",
    " 'SULA3.SA',\n",
    " 'UNIP3.SA',\n",
    " 'DOHL4.SA',\n",
    " 'EMAE4.SA',\n",
    " 'TEKA4.SA',\n",
    " 'HOOT4.SA',\n",
    " 'MTSA4.SA',\n",
    " 'BPAC5.SA',\n",
    " 'BEES4.SA',\n",
    " 'CEDO4.SA']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook \n",
    "%matplotlib inline \n",
    "\n",
    "import matplotlib.dates as mdates\n",
    "#from matplotlib.finance import candlestick_ohlc\n",
    "import datetime\n",
    "from pandas import *\n",
    "import matplotlib.mlab as mlab\n",
    "import scipy.signal as signal\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import pandas_datareader.data as pdr\n",
    "import yfinance as yf\n",
    "import datetime as dt\n",
    "import matplotlib.ticker as mticker\n",
    "from pandas_datareader import data\n",
    "import math\n",
    "import pandas_datareader as web\n",
    "from mpl_finance import candlestick_ohlc\n",
    "import pickle\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.linear_model import LinearRegression  \n",
    "import statsmodels.api as sm\n",
    "from pandas.plotting import register_matplotlib_converters\n",
    "register_matplotlib_converters()\n",
    "sns.set()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 373,
   "metadata": {},
   "outputs": [],
   "source": [
    "E_Day = 28\n",
    "E_Month = 3\n",
    "E_Year = 2021\n",
    "S_Day = 28\n",
    "S_Month = 3\n",
    "S_Year = 2020"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "def yahoo(symbols,S_Day, S_Month, S_Year, E_Day, E_Month, E_Year):\n",
    "    yf.pdr_override()       \n",
    "    stocks_yahoo = pdr.get_data_yahoo(symbols, start=datetime(S_Year, S_Month, S_Day), end=datetime(E_Year, E_Month, E_Day),   as_panel = False,)\n",
    "    return stocks_yahoo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "def download(rb):\n",
    "    stocks_all=yahoo(rb,S_Day, S_Month, S_Year, E_Day, E_Month, E_Year)\n",
    "    return stocks_all"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "def Remove(duplicate): \n",
    "    final_list = [] \n",
    "    for num in duplicate: \n",
    "        if num not in final_list: \n",
    "            final_list.append(num) \n",
    "    return final_list "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "def data_state(output):\n",
    "    plt.figure(figsize=(40,10))\n",
    "    sns.heatmap(output.isnull(),  cbar=False, cmap = 'summer')\n",
    "    print([\"Erros\",np.sum(output.isnull().sum()),\"Ativos\",len(output.columns),\"Núm. de dias\", len(output)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_prices(market_close):\n",
    "    fig = plt.subplots(figsize=(50,15))\n",
    "    ax1=plt.subplot(1,3,3)\n",
    "    market_close.plot(ax=ax1)\n",
    "    ax1.set_title('Preços em Reais',fontsize=45)\n",
    "    ax1.set_ylabel('Preço [R$]',fontsize=35)\n",
    "    ax1.set_xlabel('Dias',fontsize=35)\n",
    "    ax1.legend(loc='upper left',fontsize=15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "def normalize_prices(market_close):\n",
    "    test = market_close.copy()\n",
    "    test = test.dropna()\n",
    "    last = test.iloc[-1]\n",
    "    for i in range(len(test)):\n",
    "        test.iloc[i] = test.iloc[i]/last\n",
    "    return test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_real_returns(market_close):\n",
    "    returns = pd.DataFrame(index = market_close.iloc[0].index, columns=['returns'])\n",
    "    for i in market_close.iloc[0].index:\n",
    "        actual_price = market_close[i].iloc[-1]\n",
    "        if(math.isnan(actual_price)):\n",
    "            actual_price = market_close[i].iloc[-2]\n",
    "        last_price = market_close[i].iloc[0]\n",
    "        if(math.isnan(last_price)):\n",
    "            last_price = market_close[i].dropna()\n",
    "            last_price = last_price[0]\n",
    "        ret_real = (actual_price-last_price)/last_price \n",
    "        returns.loc[i]['returns'] = ret_real\n",
    "    return returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_risk_ret(market_close):\n",
    "    fig = plt.subplots(figsize=(50,15))\n",
    "    ax2=plt.subplot(1,3, 3) \n",
    "    colors = np.random.rand(5)\n",
    "    x = market_close.diff().dropna().std().values\n",
    "    y = get_real_returns(market_close).values\n",
    "    classes = market_close[market_close.columns].mean().values/market_close[market_close.columns].std().values\n",
    "    lbl = market_close.iloc[0].index\n",
    "\n",
    "    #Plota o diagrama de risco e retorno dos ativos\n",
    "\n",
    "    for i in range(len(x)):\n",
    "        ax2.scatter(x[i],y[i],  s=10*classes, label = market_close.iloc[0].index[i])\n",
    "        ax2.annotate(market_close.iloc[0].index[i], (x[i], y[i]))\n",
    "\n",
    "    ax2.legend(loc='upper right', fontsize=15)\n",
    "    ax2.set_xlabel(\"Risco\",fontsize=35)\n",
    "    ax2.set_ylabel('Retornos',fontsize=35)\n",
    "    ax2.set_title('Diagrama Risco Retorno',fontsize=50) \n",
    "    ax2.axhline(y=0, color='r', linestyle='-')\n",
    "\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 downloaded\n"
     ]
    }
   ],
   "source": [
    "# Coletando serie historica e calculando variaveis\n",
    "    # Ibovespa\n",
    "ibov = yahoo('^BVSP',S_Day, S_Month, S_Year, E_Day, E_Month, E_Year)\n",
    "\n",
    "# Sharpe\n",
    "def sharpe(ret_ativ, ret_free_risk, ativ_volatility):\n",
    "    s = (ret_ativ - ret_free_risk)/ativ_volatility\n",
    "    return s\n",
    "\n",
    "def analisys(stocks_all, finals_stocks):\n",
    "    \n",
    "    print(\"Insira a taxa de comparação para o Sharpe:\")\n",
    "    ret_free_risk = 0.0275 #Considerando a Taxa Selic de 2020\n",
    "    \n",
    "    index = stocks_all.index\n",
    "    stocks_close=stocks_all['Adj Close']\n",
    "    best_names = stocks_close.columns\n",
    "    \n",
    "    for i in range(len(best_names)):    \n",
    "\n",
    "            # Calculando retornos diarios e mensais dos \n",
    "\n",
    "        ativ_daily_returns = stocks_all['Adj Close'][best_names[i]].dropna().pct_change().dropna()\n",
    "        ativ_monthly_returns = stocks_all['Adj Close'][best_names[i]].dropna().resample('M').sum()\n",
    "        ativ_monthly_returns = ativ_monthly_returns.pct_change()\n",
    "        daily_values = ativ_daily_returns.copy()\n",
    "        monthly_values = ativ_monthly_returns.copy()\n",
    "\n",
    "\n",
    "        pos_days = len(daily_values[daily_values >= 0])\n",
    "        neg_days = len(daily_values[daily_values < 0])\n",
    "\n",
    "        pos_months = len(monthly_values[monthly_values >= 0])\n",
    "        neg_months = len(monthly_values[monthly_values < 0])\n",
    "\n",
    "\n",
    "        ibov_year_returns = ibov['Adj Close'].dropna().resample('Y').sum()\n",
    "        ibov_year_returns = ibov_year_returns.pct_change().dropna().mean()\n",
    "        ibov_mean = ibov['Adj Close'].dropna().mean()\n",
    "        ibov_std = ibov['Adj Close'].dropna().std()\n",
    "        ibov_year_volatility = (ibov_mean/ibov_std)\n",
    "\n",
    "\n",
    "        # Ativo\n",
    "        ativ_year_returns = stocks_all['Adj Close'][best_names[i]].dropna().resample('Y').sum()\n",
    "        ativ_year_returns = ativ_year_returns.pct_change().dropna().mean()\n",
    "        ativ_return = stocks_all['Adj Close'][best_names[i]].dropna().diff().mean()\n",
    "        ativ_std = stocks_all['Adj Close'][best_names[i]].dropna().std()\n",
    "\n",
    "        # Calculando\n",
    "        sharp = sharpe(ativ_return,ret_free_risk, ativ_std/100)\n",
    "\n",
    "\n",
    "                # TERCEIRO PLOT\n",
    "\n",
    "        log_stocks = stocks_all['Adj Close'][best_names[i]]    # Y\n",
    "        stocks_index = log_stocks.index                                 #Date\n",
    "\n",
    "        counter = None\n",
    "        x = None\n",
    "        y = None\n",
    "\n",
    "        y = log_stocks.fillna(0)\n",
    "        counter = np.arange(len(y))\n",
    "        x = counter[:]\n",
    "\n",
    "        correlacao = np.corrcoef(x,y)\n",
    "\n",
    "        x = x.reshape(-1,1)\n",
    "\n",
    "        regressor = LinearRegression()\n",
    "        regressor.fit(x,y)\n",
    "        regressor.coef_\n",
    "        reg_price = regressor.intercept_\n",
    "        coef_price = regressor.coef_[0]\n",
    "\n",
    "        base_price_1 = reg_price * (1 + coef_price)\n",
    "        target_buy_1 = stocks_all['Adj Close'][best_names[i]].iloc[-5:].mean() * (1-coef_price)\n",
    "        target_sell_1 = stocks_all['Adj Close'][best_names[i]].iloc[-5:].mean() * (1+coef_price)\n",
    "\n",
    "\n",
    "                # QUARTO PLOT\n",
    "\n",
    "        log_stocks =  stocks_all['Adj Close'][best_names[i]].pct_change() # Y\n",
    "        stocks_index = log_stocks.index\n",
    "\n",
    "        counter = None\n",
    "        x = None\n",
    "        y = None\n",
    "\n",
    "        y = log_stocks.fillna(0)\n",
    "        counter = np.arange(len(y))\n",
    "        x = counter[:]\n",
    "\n",
    "        correlacao = np.corrcoef(x,y)\n",
    "\n",
    "        x = x.reshape(-1,1)\n",
    "\n",
    "        regressor = LinearRegression()\n",
    "        regressor.fit(x,y)\n",
    "        regressor.coef_\n",
    "        reg_int = regressor.intercept_\n",
    "        coef_int = regressor.coef_[0]\n",
    "\n",
    "        base_price = reg_price * (1 + coef_int)\n",
    "        target_buy_2 = stocks_all['Adj Close'][best_names[i]].iloc[-10:].mean() * (1-coef_int)\n",
    "        target_sell_2 = stocks_all['Adj Close'][best_names[i]].iloc[-10:].mean() * (1+coef_int)\n",
    "\n",
    "        target_buy = (target_buy_1 + target_buy_2) / 2\n",
    "        target_sell = (target_sell_1 + target_sell_2) / 2\n",
    "\n",
    "        pct_up_day = 100*pos_days/(pos_days+neg_days)\n",
    "#         pct_up_month = 100*pos_months/(pos_months+neg_months)\n",
    "\n",
    "        finals_stocks['Reg_price'][best_names[i]] = reg_price\n",
    "        finals_stocks['Coef_price'][best_names[i]] = coef_price\n",
    "        finals_stocks['Reg_int'][best_names[i]] = reg_int\n",
    "        finals_stocks['Coef_int'][best_names[i]] = coef_int\n",
    "        finals_stocks['Pct_up_day'][best_names[i]] = pct_up_day\n",
    "#         finals_stocks['Pct_up_month'][best_names[i]] = pct_up_month\n",
    "        finals_stocks['Sharpe'][best_names[i]] = sharp\n",
    "        finals_stocks['Base_price'][best_names[i]] = base_price\n",
    "        finals_stocks['Target_buy'][best_names[i]] = target_buy\n",
    "        finals_stocks['Target_sell'][best_names[i]] = target_sell\n",
    "        finals_stocks['Rel_price_ret'][best_names[i]] = coef_price/coef_int\n",
    "\n",
    "        actual_price = stocks_close[best_names[i]].iloc[-1]\n",
    "        if(math.isnan(actual_price)):\n",
    "            actual_price = stocks_close[best_names[i]].iloc[-2]\n",
    "\n",
    "        finals_stocks['Actual_price'][best_names[i]] = actual_price\n",
    "        base_price = (base_price+actual_price) / 2\n",
    "\n",
    "        last_price = stocks_all['Adj Close'][best_names[i]].iloc[0]\n",
    "        if(math.isnan(last_price)):\n",
    "            last_price = stocks_all['Adj Close'][best_names[i]].dropna()\n",
    "            last_price = last_price[0]\n",
    "        ret_real = (actual_price-last_price)/last_price \n",
    "        finals_stocks['Ret_real'][best_names[i]] = ret_real*100\n",
    "        stop_loss = None\n",
    "        stop_loss = ((base_price-actual_price)/actual_price)*100\n",
    "        finals_stocks['Stop_loss'][best_names[i]] = stop_loss\n",
    "\n",
    "\n",
    "        print(\"\\n===========>\",best_names[i])\n",
    "        print()\n",
    "        print(\"------------------------------------Daily Infos--------------------------------------\")\n",
    "        print(\"Count:\")\n",
    "        print(\"              Positive - \",pos_days)\n",
    "        print(\"              Negative - \",neg_days)\n",
    "        print(\"              Pct Up   - %.2f\" % (pct_up_day))\n",
    "        print()\n",
    "        print(\"-----------------------------------Monthly Infos-------------------------------------\")\n",
    "        print(\"Count:\")\n",
    "        print(\"              Positive - \",pos_months)\n",
    "        print(\"              Negative - \",neg_months)\n",
    "#         print(\"              Pct Up   - %.2f\" % (pct_up_month))\n",
    "        print()\n",
    "        print()\n",
    "        print(\"-----------------------------------Other Infos---------------------------------------\")\n",
    "        print(\"Count:\")\n",
    "        print(\"              Sharpe      : %.3f\" % sharp)\n",
    "        print()\n",
    "        print(\"              R. price    : %.5f\" % reg_price)\n",
    "        print(\"              Coef_price  : %.8f\" % coef_price)\n",
    "        print()\n",
    "        print(\"              R. intercept: %.5f\" % reg_int)\n",
    "        print(\"              Coef        : %.8f\" % coef_int)\n",
    "        print()\n",
    "        print(\"              Target_sell : %.2f\" % target_sell)\n",
    "        print(\"              Actual_price: %.2f\" % actual_price)\n",
    "        print(\"              Target_buy  : %.2f\" % target_buy)\n",
    "        print()\n",
    "        print(\"              Base_price  : %.2f\" % base_price)\n",
    "        print(\"              Stop_loss   : %.2f\" % stop_loss + \"%\")\n",
    "        print()\n",
    "        print(\"              Stock_return: %.2f\" % (ret_real*100) + \"%\")\n",
    "        print()\n",
    "        \n",
    "    return finals_stocks  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculo do indice Sharpe\n",
    "\n",
    "ret_free_risk = 0.0275 #Considerando a Taxa Selic de 2020\n",
    "def init_analisys(best_names):\n",
    "    finals_stocks = pd.DataFrame(index = best_names[:], \n",
    "                                 columns = ['Reg_price','Coef_price','Reg_int','Coef_int','Rel_price_ret','Pct_up_day'\n",
    "                                           ,'Pct_up_month','Sharpe','Base_price','Target_buy','Target_sell','Actual_price'\n",
    "                                           ,'Ret_real','Stop_loss'])\n",
    "    return finals_stocks\n",
    "\n",
    "def plot_ohlc(df1, stocks_all, df1_price_mean, base_price, base_price_std, target_price, best_names, i):\n",
    "    fig = plt.subplots(figsize=(20,10))\n",
    "    plt.style.use('seaborn-whitegrid')\n",
    "    ax1 = plt.subplot(111)\n",
    "    ema21 = stocks_all['Adj Close'][best_names[i]].dropna().ewm(span=21, adjust=False).mean().dropna()\n",
    "    ax1.plot(ema21, color=\"red\")\n",
    "    ema80 = stocks_all['Adj Close'][best_names[i]].dropna().ewm(span=80, adjust=False).mean().dropna()\n",
    "    ax1.plot(ema80, color=\"yellow\")\n",
    "    mma200 = stocks_all['Adj Close'][best_names[i]].dropna().rolling(window=200).mean().dropna()\n",
    "    ax1.plot(mma200, color=\"blue\")\n",
    "\n",
    "    candlestick_ohlc(ax1, df1.values, width=0.8, colorup='g', colordown='r',alpha=1)\n",
    "    ax1.set_xlabel(\"Dias\",fontsize=25)\n",
    "    ax1.set_ylabel('Preços OHLC [R$]',fontsize=25)\n",
    "    ax1.set_title('Gráfico candlestick '+best_names[i], fontsize=35) \n",
    "    ax1.axhline(y=df1_price_mean, color='b', linestyle='-')\n",
    "    ax1.axhline(y=base_price, color='g', linestyle='-')\n",
    "    ax1.axhline(y=base_price_std, color='y', linestyle='-')\n",
    "    ax1.axhline(y=target_price, color='r', linestyle='-')\n",
    "    ax1.axhline(y=(1.5*target_price), color='r', linestyle='-')\n",
    "    plt.xticks(fontsize=20,rotation = 45, ha=\"right\")\n",
    "    ax1.xaxis_date()\n",
    "\n",
    "def return_line_plot(ativ_daily_returns, ativ_return_mean, best_names, i):\n",
    "    fig = plt.figure(figsize = (20,10))\n",
    "    ax1 = fig.add_axes([0.1,0.1,0.8,0.8])\n",
    "    ax1.plot(ativ_daily_returns)\n",
    "    ax1.set_xlabel(\"Data\", fontsize = 25)\n",
    "    ax1.set_ylabel(\"Retorno (Diario)\", fontsize = 25)\n",
    "    ax1.set_title('Gráfico de retorno '+best_names[i],fontsize=35) \n",
    "    ax1.axhline(y=ativ_return_mean, color='b', linestyle='-')\n",
    "    ax1.axhline(y=0, color='r', linestyle='-')\n",
    "    plt.xticks(fontsize=20,rotation = 45, ha=\"right\")\n",
    "    plt.show()    \n",
    "    \n",
    "def price_linear_regression_plot(x, y, regressor, ativ_price_mean, \n",
    "                                 base_price, base_price_std, target_price, \n",
    "                                 best_names, i):\n",
    "    fig = plt.figure(figsize = (20,10))\n",
    "    plt.scatter(x[:-1],y[:-1])\n",
    "    plt.plot(x, regressor.predict(x), color = 'red')\n",
    "    plt.axhline(y=ativ_price_mean, color='b', linestyle='-')\n",
    "    plt.axhline(y=base_price, color='g', linestyle='-')\n",
    "    plt.axhline(y=base_price_std, color='y', linestyle='-')\n",
    "    plt.axhline(y=target_price, color='r', linestyle='-')\n",
    "    plt.axhline(y=(1.5*target_price), color='r', linestyle='-')\n",
    "    plt.title('Regressao linear preços '+best_names[i], fontsize=35)\n",
    "    plt.show()\n",
    "    \n",
    "    \n",
    "def return_linear_regression_plot(x, y, regressor, ativ_return_mean, best_names, i):\n",
    "    fig = plt.figure(figsize = (20,10))\n",
    "    plt.scatter(x,y)\n",
    "    plt.plot(x, regressor.predict(x), color = 'red')\n",
    "    plt.axhline(y=ativ_return_mean, color='b', linestyle='-')\n",
    "    plt.title('Regressao linear log de retornos '+best_names[i], fontsize=35)\n",
    "    plt.show()\n",
    "\n",
    "def analisys_plot(stocks_all, finals_stocks):\n",
    "    \n",
    "    print(\"Insira a taxa de comparação para o Sharpe:\")\n",
    "    ret_free_risk = 0.0275 #Considerando a Taxa Selic de 2020\n",
    "    \n",
    "    index = stocks_all.index\n",
    "    stocks_close=stocks_all['Adj Close']\n",
    "    best_names = stocks_close.columns\n",
    "    \n",
    "    for i in range(len(best_names)):\n",
    "        \n",
    "        # Ajustes de dados\n",
    "        df1 = pd.DataFrame(index=index)\n",
    "        df1['Open']=stocks_all['Open'][best_names[i]]\n",
    "        df1['High']=stocks_all['High'][best_names[i]]\n",
    "        df1['Low']=stocks_all['Low'][best_names[i]]\n",
    "        df1['Close']=stocks_all['Close'][best_names[i]]\n",
    "        df1_price_mean=stocks_all['Close'][best_names[i]].mean()\n",
    "        df1['Volume']=stocks_all['Volume'][best_names[i]]\n",
    "\n",
    "        df1.reset_index(inplace=True)\n",
    "        df1['Date'] = df1['Date'].map(mdates.date2num)\n",
    "\n",
    "\n",
    "                #PRIMEIRO PLOT\n",
    "        print()\n",
    "        print()\n",
    "        print()\n",
    "\n",
    "\n",
    "        # Calculando retornos diarios e mensais dos ativos\n",
    "        ativ_daily_returns = stocks_all['Adj Close'][best_names[i]].dropna().pct_change().dropna()\n",
    "        ativ_mean_returns = ativ_daily_returns.mean()\n",
    "        ativ_monthly_returns = stocks_all['Adj Close'][best_names[i]].dropna().resample('M').sum()\n",
    "        ativ_monthly_returns = ativ_monthly_returns.pct_change()\n",
    "        daily_values = ativ_daily_returns.copy()\n",
    "        monthly_values = ativ_monthly_returns.copy()\n",
    "\n",
    "        pos_days = len(daily_values[daily_values >= 0])\n",
    "        neg_days = len(daily_values[daily_values < 0])\n",
    "\n",
    "        pos_months = len(monthly_values[monthly_values >= 0])\n",
    "        neg_months = len(monthly_values[monthly_values < 0])\n",
    "\n",
    "        ibov_year_returns = ibov['Adj Close'].dropna().resample('Y').sum()\n",
    "        ibov_year_returns = ibov_year_returns.pct_change().dropna().mean()\n",
    "        ibov_mean = ibov['Adj Close'].dropna().mean()\n",
    "        ibov_std = ibov['Adj Close'].dropna().std()\n",
    "        ibov_year_volatility = (ibov_mean/ibov_std)\n",
    "\n",
    "        # Ativo\n",
    "        ativ_year_returns = stocks_all['Adj Close'][best_names[i]].dropna().resample('Y').sum()\n",
    "        ativ_year_returns = ativ_year_returns.pct_change().dropna().mean()\n",
    "        ativ_return = None\n",
    "        ativ_std = None\n",
    "        ativ_return_mean = stocks_all['Adj Close'][best_names[i]].pct_change().mean()\n",
    "        ativ_price_mean = stocks_all['Adj Close'][best_names[i]].mean()\n",
    "        ativ_std = stocks_all['Adj Close'][best_names[i]].dropna().std()\n",
    "\n",
    "        # Calculando\n",
    "        sharp = sharpe(ativ_return_mean,ret_free_risk, (ativ_std/100))\n",
    "\n",
    "        \n",
    "                # SEGUNDO PLOT\n",
    "\n",
    "                # TERCEIRO PLOT\n",
    "        log_stocks = stocks_all['Adj Close'][best_names[i]]    # Y\n",
    "        if(log_stocks.iloc[-1] == 0):\n",
    "            log_stocks = log_stocks.iloc[:-1]\n",
    "        stocks_index = log_stocks.index                                 #Date\n",
    "\n",
    "        counter = None\n",
    "        x = None\n",
    "        y = None\n",
    "\n",
    "        y = log_stocks.fillna(0)\n",
    "        y_mean = y.mean()\n",
    "        counter = np.arange(len(y))\n",
    "        x = counter[:]\n",
    "\n",
    "        correlacao = np.corrcoef(x,y)\n",
    "\n",
    "        x = x.reshape(-1,1)\n",
    "\n",
    "        regressor = LinearRegression()\n",
    "        regressor.fit(x,y)\n",
    "        regressor.coef_\n",
    "        reg_price = regressor.intercept_\n",
    "        coef_price = regressor.coef_[0]\n",
    "\n",
    "        target_buy_1 = stocks_all['Adj Close'][best_names[i]].iloc[-5:].mean() * (1-coef_price)\n",
    "        target_sell_1 = stocks_all['Adj Close'][best_names[i]].iloc[-5:].mean() * (1+coef_price)\n",
    "\n",
    "\n",
    "                # QUARTO PLOT\n",
    "        log_stocks_return =  stocks_all['Adj Close'][best_names[i]].pct_change() # Y\n",
    "        if(log_stocks_return.iloc[-1] == 0):\n",
    "            log_stocks_return = log_stocks_return.iloc[:-2]\n",
    "        stocks_index = log_stocks_return.index\n",
    "\n",
    "        counter_return = None\n",
    "        x_return = None\n",
    "        y_return = None\n",
    "\n",
    "        y_return = log_stocks_return.fillna(0)\n",
    "        y_mean_return = y_return.mean()\n",
    "        counter_return = np.arange(len(y_return))\n",
    "        x_return = counter_return[:]\n",
    "\n",
    "        correlacao_return = np.corrcoef(x_return,y_return)\n",
    "\n",
    "        x_return = x_return.reshape(-1,1)\n",
    "\n",
    "        regressor_return = LinearRegression()\n",
    "        regressor_return.fit(x_return,y_return)\n",
    "        regressor_return.coef_\n",
    "        reg_int_return = regressor_return.intercept_\n",
    "        coef_int_return = regressor_return.coef_[0]\n",
    "\n",
    "        base_price = reg_price * (1 + coef_price)\n",
    "        base_price_std = reg_price * (1 + (ativ_std/10))\n",
    "        target_buy_2 = stocks_close[best_names[i]].iloc[-10:].mean() * (1-coef_int_return)\n",
    "        target_sell_2 = stocks_close[best_names[i]].iloc[-10:].mean() * (1+coef_int_return)\n",
    "\n",
    "        target_buy = (target_buy_1 + target_buy_2) / 2\n",
    "        target_sell = (target_sell_1 + target_sell_2) / 2\n",
    "\n",
    "        pct_up_day = 100*pos_days/(pos_days+neg_days)\n",
    "        pct_up_month = 100*pos_months/(pos_months+neg_months)\n",
    "\n",
    "        finals_stocks['Reg_price'][best_names[i]] = reg_price\n",
    "        finals_stocks['Coef_price'][best_names[i]] = coef_price\n",
    "        finals_stocks['Reg_int'][best_names[i]] = reg_int_return\n",
    "        finals_stocks['Coef_int'][best_names[i]] = coef_int_return\n",
    "        finals_stocks['Pct_up_day'][best_names[i]] = pct_up_day\n",
    "        finals_stocks['Pct_up_month'][best_names[i]] = pct_up_month\n",
    "        finals_stocks['Sharpe'][best_names[i]] = sharp\n",
    "        finals_stocks['Target_buy'][best_names[i]] = target_buy\n",
    "        finals_stocks['Target_sell'][best_names[i]] = target_sell\n",
    "        finals_stocks['Rel_price_ret'][best_names[i]] = coef_price/coef_int_return\n",
    "\n",
    "        actual_price = stocks_close[best_names[i]].iloc[-1]\n",
    "        if(math.isnan(actual_price)):\n",
    "            actual_price = stocks_close[best_names[i]].iloc[-2]\n",
    "\n",
    "        finals_stocks['Actual_price'][best_names[i]] = actual_price\n",
    "        base_price = (base_price+actual_price) / 2\n",
    "        base_price_std = (base_price_std+actual_price) / 2\n",
    "        target_price = 2*(base_price_std - base_price) + base_price_std\n",
    "\n",
    "        last_price = stocks_all['Adj Close'][best_names[i]].iloc[0]\n",
    "        if(math.isnan(last_price)):\n",
    "            last_price = stocks_all['Adj Close'][best_names[i]].dropna()\n",
    "            last_price = last_price[0]\n",
    "        ret_real = (actual_price-last_price)/last_price \n",
    "        finals_stocks['Ret_real'][best_names[i]] = ret_real*100\n",
    "        stop_loss = None\n",
    "        stop_loss = ((base_price-actual_price)/actual_price)*100\n",
    "        finals_stocks['Stop_loss'][best_names[i]] = stop_loss\n",
    "\n",
    "#         Plots\n",
    "        plot_ohlc(df1, stocks_all, df1_price_mean, \n",
    "                  base_price, base_price_std, target_price, \n",
    "                  best_names, i)\n",
    "        return_line_plot(ativ_daily_returns, ativ_return_mean, best_names, i) \n",
    "        price_linear_regression_plot(x, y, regressor, ativ_price_mean, \n",
    "                                     base_price, base_price_std, target_price,\n",
    "                                     best_names, i)\n",
    "        return_linear_regression_plot(x_return, y_return, regressor_return, ativ_return_mean, best_names, i)\n",
    "        df1 = None\n",
    "        \n",
    "        \n",
    "        print(\"\\n===========>\",best_names[i])\n",
    "        print()\n",
    "        print(\"------------------------------------Daily Infos--------------------------------------\")\n",
    "        print(\"Count:\")\n",
    "        print(\"              Positive - \",pos_days)\n",
    "        print(\"              Negative - \",neg_days)\n",
    "        print(\"              Pct Up   - %.2f\" % (pct_up_day))\n",
    "        print()\n",
    "        print(\"-----------------------------------Monthly Infos-------------------------------------\")\n",
    "        print(\"Count:\")\n",
    "        print(\"              Positive - \",pos_months)\n",
    "        print(\"              Negative - \",neg_months)\n",
    "        print(\"              Pct Up   - %.2f\" % (pct_up_month))\n",
    "        print()\n",
    "        print()\n",
    "        print(\"-----------------------------------Other Infos---------------------------------------\")\n",
    "        print(\"Count:\")\n",
    "        print(\"              Sharpe      : %.3f\" % sharp)\n",
    "        print()\n",
    "        print(\"              R. price    : %.5f\" % reg_price)\n",
    "        print(\"              Coef_price  : %.8f\" % coef_price)\n",
    "        print()\n",
    "        print(\"              R. intercept: %.5f\" % reg_int_return)\n",
    "        print(\"              Coef        : %.8f\" % coef_int_return)\n",
    "        print()\n",
    "        print(\"              Target_sell : %.2f\" % target_sell)\n",
    "        print(\"              Actual_price: %.2f\" % actual_price)\n",
    "        print(\"              Target_buy  : %.2f\" % target_buy)\n",
    "        print()\n",
    "        print(\"              Base_price  : %.2f\" % base_price)\n",
    "        print(\"              Stop_loss   : %.2f\" % stop_loss + \"%\")\n",
    "        print()\n",
    "        print(\"              Ativ_return : %.2f\" % (ret_real*100) + \"%\")\n",
    "        print()\n",
    "        \n",
    "    return finals_stocks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "def routine(best_names):\n",
    "    finals_stocks = init_analisys(stocks_all['Close'][best_names].columns)\n",
    "    analisys(stocks_all, finals_stocks)\n",
    "    return finals_stocks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "def routine_plot(best_names):\n",
    "    finals_stocks = init_analisys(stocks_all['Close'][best_names].columns)\n",
    "    analisys_plot(stocks_all, finals_stocks)\n",
    "    return finals_stocks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "def best_volumes(all_names, qtd):\n",
    "    market_all=yahoo(all_names,S_Day, S_Month, S_Year, E_Day, E_Month, E_Year)\n",
    "    market_close=market_all['Adj Close']\n",
    "    lista=market_all['Volume'].mean().sort_values(ascending = False)[:qtd].index\n",
    "    names = []\n",
    "    for i in range(0, len(lista)):\n",
    "        names.append(lista[i]) \n",
    "    market_all = market_all[market_close.isin(names)]\n",
    "    return market_all"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "# all_names = ['BRAP4.SA','ENEV3.SA','GGBR4.SA','IVVB11.SA',\n",
    "#              'LCAM3.SA','LWSA3.SA','MGLU3.SA','NGRD3.SA','PRIO3.SA','SUZB3.SA',\n",
    "#              'WEGE3.SA']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "<div id=\"Tópico 1\">\n",
    "    <div class=\"alert alert-block alert-info\" style=\"margin-top: 0px\"> \n",
    "</div> </div> "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Analise dos N ativos com maior volume negociado</h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 374,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  299 of 299 downloaded\n"
     ]
    }
   ],
   "source": [
    "market=yahoo(all_names,S_Day, S_Month, S_Year, E_Day, E_Month, E_Year)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 375,
   "metadata": {},
   "outputs": [],
   "source": [
    "lista = list(market['Volume'].median().sort_values(ascending = False)[:150].index)\n",
    "market_all = market.copy()\n",
    "stocks_drop = all_names.copy()\n",
    "for name in lista:\n",
    "    stocks_drop.remove(name)\n",
    "market_close=market_all['Adj Close'].drop(columns=stocks_drop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 376,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ABEV3.SA</th>\n",
       "      <th>AERI3.SA</th>\n",
       "      <th>ALPA4.SA</th>\n",
       "      <th>ALSO3.SA</th>\n",
       "      <th>AMAR3.SA</th>\n",
       "      <th>ANIM3.SA</th>\n",
       "      <th>AZUL4.SA</th>\n",
       "      <th>B3SA3.SA</th>\n",
       "      <th>BBAS3.SA</th>\n",
       "      <th>BBDC3.SA</th>\n",
       "      <th>...</th>\n",
       "      <th>TOTS3.SA</th>\n",
       "      <th>TRIS3.SA</th>\n",
       "      <th>TRPL4.SA</th>\n",
       "      <th>UGPA3.SA</th>\n",
       "      <th>USIM5.SA</th>\n",
       "      <th>VALE3.SA</th>\n",
       "      <th>VIVA3.SA</th>\n",
       "      <th>VVAR3.SA</th>\n",
       "      <th>WEGE3.SA</th>\n",
       "      <th>YDUQ3.SA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <th>ABEV3.SA</th>\n",
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       "      <td>0.425000</td>\n",
       "      <td>0.346233</td>\n",
       "      <td>0.310454</td>\n",
       "      <td>0.402720</td>\n",
       "      <td>0.424210</td>\n",
       "      <td>0.568497</td>\n",
       "      <td>0.624730</td>\n",
       "      <td>...</td>\n",
       "      <td>0.250331</td>\n",
       "      <td>0.376912</td>\n",
       "      <td>0.317283</td>\n",
       "      <td>0.494798</td>\n",
       "      <td>0.319783</td>\n",
       "      <td>0.220859</td>\n",
       "      <td>0.471905</td>\n",
       "      <td>0.253505</td>\n",
       "      <td>0.337792</td>\n",
       "      <td>0.471294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AERI3.SA</th>\n",
       "      <td>0.130357</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.177212</td>\n",
       "      <td>0.168305</td>\n",
       "      <td>0.223260</td>\n",
       "      <td>0.114943</td>\n",
       "      <td>0.274572</td>\n",
       "      <td>0.214604</td>\n",
       "      <td>0.191074</td>\n",
       "      <td>0.218975</td>\n",
       "      <td>...</td>\n",
       "      <td>0.037322</td>\n",
       "      <td>0.185700</td>\n",
       "      <td>0.225195</td>\n",
       "      <td>0.256135</td>\n",
       "      <td>0.096066</td>\n",
       "      <td>0.007395</td>\n",
       "      <td>0.147076</td>\n",
       "      <td>0.237632</td>\n",
       "      <td>0.193966</td>\n",
       "      <td>0.218626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALPA4.SA</th>\n",
       "      <td>0.283051</td>\n",
       "      <td>0.177212</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.436558</td>\n",
       "      <td>0.407595</td>\n",
       "      <td>0.423060</td>\n",
       "      <td>0.329780</td>\n",
       "      <td>0.424040</td>\n",
       "      <td>0.325419</td>\n",
       "      <td>0.326771</td>\n",
       "      <td>...</td>\n",
       "      <td>0.337021</td>\n",
       "      <td>0.418931</td>\n",
       "      <td>0.319789</td>\n",
       "      <td>0.379642</td>\n",
       "      <td>0.216358</td>\n",
       "      <td>0.055889</td>\n",
       "      <td>0.486406</td>\n",
       "      <td>0.284553</td>\n",
       "      <td>0.353214</td>\n",
       "      <td>0.384966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALSO3.SA</th>\n",
       "      <td>0.425000</td>\n",
       "      <td>0.168305</td>\n",
       "      <td>0.436558</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.592428</td>\n",
       "      <td>0.461950</td>\n",
       "      <td>0.589075</td>\n",
       "      <td>0.495238</td>\n",
       "      <td>0.607750</td>\n",
       "      <td>0.628556</td>\n",
       "      <td>...</td>\n",
       "      <td>0.365894</td>\n",
       "      <td>0.658830</td>\n",
       "      <td>0.340378</td>\n",
       "      <td>0.550140</td>\n",
       "      <td>0.236166</td>\n",
       "      <td>0.149611</td>\n",
       "      <td>0.558100</td>\n",
       "      <td>0.443484</td>\n",
       "      <td>0.230735</td>\n",
       "      <td>0.549408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMAR3.SA</th>\n",
       "      <td>0.346233</td>\n",
       "      <td>0.223260</td>\n",
       "      <td>0.407595</td>\n",
       "      <td>0.592428</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.508808</td>\n",
       "      <td>0.480475</td>\n",
       "      <td>0.427833</td>\n",
       "      <td>0.476953</td>\n",
       "      <td>0.444859</td>\n",
       "      <td>...</td>\n",
       "      <td>0.330376</td>\n",
       "      <td>0.709588</td>\n",
       "      <td>0.190449</td>\n",
       "      <td>0.435800</td>\n",
       "      <td>0.273988</td>\n",
       "      <td>0.032308</td>\n",
       "      <td>0.592988</td>\n",
       "      <td>0.490582</td>\n",
       "      <td>0.263656</td>\n",
       "      <td>0.618716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ANIM3.SA</th>\n",
       "      <td>0.310454</td>\n",
       "      <td>0.114943</td>\n",
       "      <td>0.423060</td>\n",
       "      <td>0.461950</td>\n",
       "      <td>0.508808</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.344041</td>\n",
       "      <td>0.396803</td>\n",
       "      <td>0.390703</td>\n",
       "      <td>0.375097</td>\n",
       "      <td>...</td>\n",
       "      <td>0.371036</td>\n",
       "      <td>0.490145</td>\n",
       "      <td>0.260704</td>\n",
       "      <td>0.373479</td>\n",
       "      <td>0.285327</td>\n",
       "      <td>0.064754</td>\n",
       "      <td>0.429799</td>\n",
       "      <td>0.387079</td>\n",
       "      <td>0.295470</td>\n",
       "      <td>0.534941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AZUL4.SA</th>\n",
       "      <td>0.402720</td>\n",
       "      <td>0.274572</td>\n",
       "      <td>0.329780</td>\n",
       "      <td>0.589075</td>\n",
       "      <td>0.480475</td>\n",
       "      <td>0.344041</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.381688</td>\n",
       "      <td>0.563973</td>\n",
       "      <td>0.573759</td>\n",
       "      <td>...</td>\n",
       "      <td>0.225213</td>\n",
       "      <td>0.514326</td>\n",
       "      <td>0.291341</td>\n",
       "      <td>0.439771</td>\n",
       "      <td>0.372027</td>\n",
       "      <td>0.169001</td>\n",
       "      <td>0.486329</td>\n",
       "      <td>0.367273</td>\n",
       "      <td>0.184805</td>\n",
       "      <td>0.494654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B3SA3.SA</th>\n",
       "      <td>0.424210</td>\n",
       "      <td>0.214604</td>\n",
       "      <td>0.424040</td>\n",
       "      <td>0.495238</td>\n",
       "      <td>0.427833</td>\n",
       "      <td>0.396803</td>\n",
       "      <td>0.381688</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.546217</td>\n",
       "      <td>0.533654</td>\n",
       "      <td>...</td>\n",
       "      <td>0.492184</td>\n",
       "      <td>0.536870</td>\n",
       "      <td>0.341926</td>\n",
       "      <td>0.495214</td>\n",
       "      <td>0.320611</td>\n",
       "      <td>0.212417</td>\n",
       "      <td>0.498249</td>\n",
       "      <td>0.475400</td>\n",
       "      <td>0.462275</td>\n",
       "      <td>0.449871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BBAS3.SA</th>\n",
       "      <td>0.568497</td>\n",
       "      <td>0.191074</td>\n",
       "      <td>0.325419</td>\n",
       "      <td>0.607750</td>\n",
       "      <td>0.476953</td>\n",
       "      <td>0.390703</td>\n",
       "      <td>0.563973</td>\n",
       "      <td>0.546217</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.892512</td>\n",
       "      <td>...</td>\n",
       "      <td>0.300798</td>\n",
       "      <td>0.566172</td>\n",
       "      <td>0.394337</td>\n",
       "      <td>0.582971</td>\n",
       "      <td>0.418089</td>\n",
       "      <td>0.304232</td>\n",
       "      <td>0.492367</td>\n",
       "      <td>0.484123</td>\n",
       "      <td>0.280515</td>\n",
       "      <td>0.475466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BBDC3.SA</th>\n",
       "      <td>0.624730</td>\n",
       "      <td>0.218975</td>\n",
       "      <td>0.326771</td>\n",
       "      <td>0.628556</td>\n",
       "      <td>0.444859</td>\n",
       "      <td>0.375097</td>\n",
       "      <td>0.573759</td>\n",
       "      <td>0.533654</td>\n",
       "      <td>0.892512</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.234106</td>\n",
       "      <td>0.510220</td>\n",
       "      <td>0.384304</td>\n",
       "      <td>0.594559</td>\n",
       "      <td>0.420055</td>\n",
       "      <td>0.361119</td>\n",
       "      <td>0.535364</td>\n",
       "      <td>0.376597</td>\n",
       "      <td>0.269855</td>\n",
       "      <td>0.492510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BBDC4.SA</th>\n",
       "      <td>0.642411</td>\n",
       "      <td>0.212805</td>\n",
       "      <td>0.309654</td>\n",
       "      <td>0.612613</td>\n",
       "      <td>0.429129</td>\n",
       "      <td>0.344736</td>\n",
       "      <td>0.576639</td>\n",
       "      <td>0.491570</td>\n",
       "      <td>0.876182</td>\n",
       "      <td>0.970756</td>\n",
       "      <td>...</td>\n",
       "      <td>0.179817</td>\n",
       "      <td>0.478835</td>\n",
       "      <td>0.370205</td>\n",
       "      <td>0.583470</td>\n",
       "      <td>0.405252</td>\n",
       "      <td>0.359996</td>\n",
       "      <td>0.512106</td>\n",
       "      <td>0.349123</td>\n",
       "      <td>0.216587</td>\n",
       "      <td>0.478712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BBSE3.SA</th>\n",
       "      <td>0.489181</td>\n",
       "      <td>0.226997</td>\n",
       "      <td>0.394964</td>\n",
       "      <td>0.528830</td>\n",
       "      <td>0.560273</td>\n",
       "      <td>0.452708</td>\n",
       "      <td>0.440024</td>\n",
       "      <td>0.538062</td>\n",
       "      <td>0.608050</td>\n",
       "      <td>0.610447</td>\n",
       "      <td>...</td>\n",
       "      <td>0.417267</td>\n",
       "      <td>0.572240</td>\n",
       "      <td>0.342205</td>\n",
       "      <td>0.546492</td>\n",
       "      <td>0.335124</td>\n",
       "      <td>0.198430</td>\n",
       "      <td>0.523842</td>\n",
       "      <td>0.440609</td>\n",
       "      <td>0.371867</td>\n",
       "      <td>0.555146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BEEF3.SA</th>\n",
       "      <td>0.116238</td>\n",
       "      <td>0.123551</td>\n",
       "      <td>0.047214</td>\n",
       "      <td>0.043556</td>\n",
       "      <td>-0.059209</td>\n",
       "      <td>0.054806</td>\n",
       "      <td>-0.095907</td>\n",
       "      <td>0.129839</td>\n",
       "      <td>0.074578</td>\n",
       "      <td>0.058067</td>\n",
       "      <td>...</td>\n",
       "      <td>0.114514</td>\n",
       "      <td>-0.106063</td>\n",
       "      <td>0.143212</td>\n",
       "      <td>0.152114</td>\n",
       "      <td>0.072070</td>\n",
       "      <td>0.141695</td>\n",
       "      <td>0.021456</td>\n",
       "      <td>0.208817</td>\n",
       "      <td>0.132631</td>\n",
       "      <td>-0.019768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BIDI4.SA</th>\n",
       "      <td>0.267361</td>\n",
       "      <td>0.194437</td>\n",
       "      <td>0.214704</td>\n",
       "      <td>0.285123</td>\n",
       "      <td>0.271282</td>\n",
       "      <td>0.257797</td>\n",
       "      <td>0.197584</td>\n",
       "      <td>0.307090</td>\n",
       "      <td>0.242458</td>\n",
       "      <td>0.203714</td>\n",
       "      <td>...</td>\n",
       "      <td>0.350452</td>\n",
       "      <td>0.349461</td>\n",
       "      <td>0.188540</td>\n",
       "      <td>0.213853</td>\n",
       "      <td>0.120762</td>\n",
       "      <td>0.057293</td>\n",
       "      <td>0.248729</td>\n",
       "      <td>0.381075</td>\n",
       "      <td>0.343658</td>\n",
       "      <td>0.199483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BKBR3.SA</th>\n",
       "      <td>0.350399</td>\n",
       "      <td>0.255859</td>\n",
       "      <td>0.234580</td>\n",
       "      <td>0.450903</td>\n",
       "      <td>0.547001</td>\n",
       "      <td>0.424125</td>\n",
       "      <td>0.435047</td>\n",
       "      <td>0.369288</td>\n",
       "      <td>0.379855</td>\n",
       "      <td>0.349280</td>\n",
       "      <td>...</td>\n",
       "      <td>0.297177</td>\n",
       "      <td>0.483587</td>\n",
       "      <td>0.243675</td>\n",
       "      <td>0.350253</td>\n",
       "      <td>0.302591</td>\n",
       "      <td>0.039182</td>\n",
       "      <td>0.435197</td>\n",
       "      <td>0.368263</td>\n",
       "      <td>0.217056</td>\n",
       "      <td>0.381174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BMGB4.SA</th>\n",
       "      <td>0.405669</td>\n",
       "      <td>0.130594</td>\n",
       "      <td>0.268647</td>\n",
       "      <td>0.472417</td>\n",
       "      <td>0.508713</td>\n",
       "      <td>0.311234</td>\n",
       "      <td>0.422801</td>\n",
       "      <td>0.388643</td>\n",
       "      <td>0.508576</td>\n",
       "      <td>0.507922</td>\n",
       "      <td>...</td>\n",
       "      <td>0.262823</td>\n",
       "      <td>0.538495</td>\n",
       "      <td>0.287214</td>\n",
       "      <td>0.402902</td>\n",
       "      <td>0.291914</td>\n",
       "      <td>0.112417</td>\n",
       "      <td>0.475470</td>\n",
       "      <td>0.335984</td>\n",
       "      <td>0.208978</td>\n",
       "      <td>0.366185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BPAC11.SA</th>\n",
       "      <td>0.347235</td>\n",
       "      <td>0.217739</td>\n",
       "      <td>0.469102</td>\n",
       "      <td>0.567655</td>\n",
       "      <td>0.513351</td>\n",
       "      <td>0.358054</td>\n",
       "      <td>0.497027</td>\n",
       "      <td>0.625072</td>\n",
       "      <td>0.549920</td>\n",
       "      <td>0.536951</td>\n",
       "      <td>...</td>\n",
       "      <td>0.446725</td>\n",
       "      <td>0.630288</td>\n",
       "      <td>0.318435</td>\n",
       "      <td>0.503464</td>\n",
       "      <td>0.308163</td>\n",
       "      <td>0.156336</td>\n",
       "      <td>0.562010</td>\n",
       "      <td>0.491691</td>\n",
       "      <td>0.389276</td>\n",
       "      <td>0.485179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BPAN4.SA</th>\n",
       "      <td>-0.064777</td>\n",
       "      <td>-0.052091</td>\n",
       "      <td>0.003605</td>\n",
       "      <td>0.051187</td>\n",
       "      <td>0.076989</td>\n",
       "      <td>0.072805</td>\n",
       "      <td>0.006770</td>\n",
       "      <td>-0.026151</td>\n",
       "      <td>-0.167320</td>\n",
       "      <td>-0.058150</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.095737</td>\n",
       "      <td>0.098609</td>\n",
       "      <td>-0.108704</td>\n",
       "      <td>-0.018030</td>\n",
       "      <td>0.046383</td>\n",
       "      <td>-0.007375</td>\n",
       "      <td>0.048998</td>\n",
       "      <td>-0.042647</td>\n",
       "      <td>-0.029522</td>\n",
       "      <td>0.001793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BRAP4.SA</th>\n",
       "      <td>0.231836</td>\n",
       "      <td>0.019969</td>\n",
       "      <td>0.099214</td>\n",
       "      <td>0.146265</td>\n",
       "      <td>0.023511</td>\n",
       "      <td>0.085884</td>\n",
       "      <td>0.158613</td>\n",
       "      <td>0.231783</td>\n",
       "      <td>0.272145</td>\n",
       "      <td>0.325777</td>\n",
       "      <td>...</td>\n",
       "      <td>0.074007</td>\n",
       "      <td>0.059414</td>\n",
       "      <td>0.140123</td>\n",
       "      <td>0.262200</td>\n",
       "      <td>0.497682</td>\n",
       "      <td>0.901751</td>\n",
       "      <td>0.170482</td>\n",
       "      <td>0.035451</td>\n",
       "      <td>0.243500</td>\n",
       "      <td>0.155792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BRDT3.SA</th>\n",
       "      <td>0.527924</td>\n",
       "      <td>0.087028</td>\n",
       "      <td>0.449752</td>\n",
       "      <td>0.622095</td>\n",
       "      <td>0.524699</td>\n",
       "      <td>0.389427</td>\n",
       "      <td>0.467207</td>\n",
       "      <td>0.583560</td>\n",
       "      <td>0.659330</td>\n",
       "      <td>0.657639</td>\n",
       "      <td>...</td>\n",
       "      <td>0.436375</td>\n",
       "      <td>0.579869</td>\n",
       "      <td>0.321044</td>\n",
       "      <td>0.706007</td>\n",
       "      <td>0.294432</td>\n",
       "      <td>0.220798</td>\n",
       "      <td>0.538563</td>\n",
       "      <td>0.457813</td>\n",
       "      <td>0.332309</td>\n",
       "      <td>0.551218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BRFS3.SA</th>\n",
       "      <td>0.270158</td>\n",
       "      <td>0.169293</td>\n",
       "      <td>0.098508</td>\n",
       "      <td>0.286966</td>\n",
       "      <td>0.067618</td>\n",
       "      <td>0.178562</td>\n",
       "      <td>0.190293</td>\n",
       "      <td>0.208612</td>\n",
       "      <td>0.349708</td>\n",
       "      <td>0.335743</td>\n",
       "      <td>...</td>\n",
       "      <td>0.251088</td>\n",
       "      <td>0.088448</td>\n",
       "      <td>0.267316</td>\n",
       "      <td>0.334911</td>\n",
       "      <td>0.151987</td>\n",
       "      <td>0.240274</td>\n",
       "      <td>0.196696</td>\n",
       "      <td>0.250501</td>\n",
       "      <td>0.152311</td>\n",
       "      <td>0.102571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BRKM5.SA</th>\n",
       "      <td>0.330664</td>\n",
       "      <td>0.085338</td>\n",
       "      <td>0.245153</td>\n",
       "      <td>0.213484</td>\n",
       "      <td>0.166790</td>\n",
       "      <td>0.246415</td>\n",
       "      <td>0.293355</td>\n",
       "      <td>0.294789</td>\n",
       "      <td>0.339461</td>\n",
       "      <td>0.366027</td>\n",
       "      <td>...</td>\n",
       "      <td>0.197415</td>\n",
       "      <td>0.204558</td>\n",
       "      <td>0.319444</td>\n",
       "      <td>0.318575</td>\n",
       "      <td>0.390667</td>\n",
       "      <td>0.212556</td>\n",
       "      <td>0.398119</td>\n",
       "      <td>0.332190</td>\n",
       "      <td>0.176952</td>\n",
       "      <td>0.253295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BRML3.SA</th>\n",
       "      <td>0.439156</td>\n",
       "      <td>0.085328</td>\n",
       "      <td>0.376454</td>\n",
       "      <td>0.879162</td>\n",
       "      <td>0.576875</td>\n",
       "      <td>0.441785</td>\n",
       "      <td>0.614909</td>\n",
       "      <td>0.514477</td>\n",
       "      <td>0.602402</td>\n",
       "      <td>0.617651</td>\n",
       "      <td>...</td>\n",
       "      <td>0.367369</td>\n",
       "      <td>0.635251</td>\n",
       "      <td>0.277585</td>\n",
       "      <td>0.532644</td>\n",
       "      <td>0.288941</td>\n",
       "      <td>0.141861</td>\n",
       "      <td>0.526896</td>\n",
       "      <td>0.459285</td>\n",
       "      <td>0.232413</td>\n",
       "      <td>0.533000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BRPR3.SA</th>\n",
       "      <td>0.476427</td>\n",
       "      <td>0.144513</td>\n",
       "      <td>0.364461</td>\n",
       "      <td>0.727617</td>\n",
       "      <td>0.536390</td>\n",
       "      <td>0.411086</td>\n",
       "      <td>0.582699</td>\n",
       "      <td>0.459528</td>\n",
       "      <td>0.529902</td>\n",
       "      <td>0.538350</td>\n",
       "      <td>...</td>\n",
       "      <td>0.350813</td>\n",
       "      <td>0.581471</td>\n",
       "      <td>0.270340</td>\n",
       "      <td>0.457412</td>\n",
       "      <td>0.294319</td>\n",
       "      <td>0.130236</td>\n",
       "      <td>0.512757</td>\n",
       "      <td>0.476062</td>\n",
       "      <td>0.298429</td>\n",
       "      <td>0.510320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BRSR6.SA</th>\n",
       "      <td>0.520014</td>\n",
       "      <td>0.288650</td>\n",
       "      <td>0.249216</td>\n",
       "      <td>0.544614</td>\n",
       "      <td>0.513564</td>\n",
       "      <td>0.385575</td>\n",
       "      <td>0.528392</td>\n",
       "      <td>0.460483</td>\n",
       "      <td>0.731650</td>\n",
       "      <td>0.765500</td>\n",
       "      <td>...</td>\n",
       "      <td>0.257249</td>\n",
       "      <td>0.523723</td>\n",
       "      <td>0.384218</td>\n",
       "      <td>0.538351</td>\n",
       "      <td>0.386693</td>\n",
       "      <td>0.263250</td>\n",
       "      <td>0.504362</td>\n",
       "      <td>0.397018</td>\n",
       "      <td>0.176333</td>\n",
       "      <td>0.514096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BTOW3.SA</th>\n",
       "      <td>0.210269</td>\n",
       "      <td>0.279530</td>\n",
       "      <td>0.261045</td>\n",
       "      <td>0.275801</td>\n",
       "      <td>0.192967</td>\n",
       "      <td>0.283450</td>\n",
       "      <td>0.141325</td>\n",
       "      <td>0.324521</td>\n",
       "      <td>0.165910</td>\n",
       "      <td>0.132757</td>\n",
       "      <td>...</td>\n",
       "      <td>0.415645</td>\n",
       "      <td>0.234886</td>\n",
       "      <td>0.169975</td>\n",
       "      <td>0.240747</td>\n",
       "      <td>0.111015</td>\n",
       "      <td>0.048684</td>\n",
       "      <td>0.232337</td>\n",
       "      <td>0.514076</td>\n",
       "      <td>0.398324</td>\n",
       "      <td>0.216062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAML3.SA</th>\n",
       "      <td>0.287550</td>\n",
       "      <td>0.228125</td>\n",
       "      <td>0.278213</td>\n",
       "      <td>0.330043</td>\n",
       "      <td>0.254254</td>\n",
       "      <td>0.330328</td>\n",
       "      <td>0.149942</td>\n",
       "      <td>0.384746</td>\n",
       "      <td>0.286401</td>\n",
       "      <td>0.295661</td>\n",
       "      <td>...</td>\n",
       "      <td>0.374057</td>\n",
       "      <td>0.249878</td>\n",
       "      <td>0.229530</td>\n",
       "      <td>0.308516</td>\n",
       "      <td>0.228651</td>\n",
       "      <td>0.147389</td>\n",
       "      <td>0.224881</td>\n",
       "      <td>0.305848</td>\n",
       "      <td>0.309838</td>\n",
       "      <td>0.288093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CASH3.SA</th>\n",
       "      <td>0.123295</td>\n",
       "      <td>0.329927</td>\n",
       "      <td>0.340290</td>\n",
       "      <td>0.169034</td>\n",
       "      <td>0.233588</td>\n",
       "      <td>0.155630</td>\n",
       "      <td>0.237897</td>\n",
       "      <td>0.185601</td>\n",
       "      <td>0.168435</td>\n",
       "      <td>0.063781</td>\n",
       "      <td>...</td>\n",
       "      <td>0.185417</td>\n",
       "      <td>0.185198</td>\n",
       "      <td>0.250188</td>\n",
       "      <td>0.234508</td>\n",
       "      <td>0.156851</td>\n",
       "      <td>0.042035</td>\n",
       "      <td>0.176511</td>\n",
       "      <td>0.220557</td>\n",
       "      <td>0.255564</td>\n",
       "      <td>0.138597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CCRO3.SA</th>\n",
       "      <td>0.422174</td>\n",
       "      <td>0.240019</td>\n",
       "      <td>0.393796</td>\n",
       "      <td>0.594058</td>\n",
       "      <td>0.527209</td>\n",
       "      <td>0.350284</td>\n",
       "      <td>0.495258</td>\n",
       "      <td>0.592153</td>\n",
       "      <td>0.608991</td>\n",
       "      <td>0.603977</td>\n",
       "      <td>...</td>\n",
       "      <td>0.339438</td>\n",
       "      <td>0.574684</td>\n",
       "      <td>0.349060</td>\n",
       "      <td>0.590714</td>\n",
       "      <td>0.287641</td>\n",
       "      <td>0.193505</td>\n",
       "      <td>0.450750</td>\n",
       "      <td>0.391743</td>\n",
       "      <td>0.265839</td>\n",
       "      <td>0.478343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CEAB3.SA</th>\n",
       "      <td>0.381106</td>\n",
       "      <td>0.167113</td>\n",
       "      <td>0.390066</td>\n",
       "      <td>0.573841</td>\n",
       "      <td>0.626454</td>\n",
       "      <td>0.469403</td>\n",
       "      <td>0.540569</td>\n",
       "      <td>0.379141</td>\n",
       "      <td>0.477003</td>\n",
       "      <td>0.508402</td>\n",
       "      <td>...</td>\n",
       "      <td>0.368862</td>\n",
       "      <td>0.569818</td>\n",
       "      <td>0.249201</td>\n",
       "      <td>0.455648</td>\n",
       "      <td>0.315325</td>\n",
       "      <td>0.088981</td>\n",
       "      <td>0.540654</td>\n",
       "      <td>0.431328</td>\n",
       "      <td>0.283205</td>\n",
       "      <td>0.575905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RANI3.SA</th>\n",
       "      <td>-0.012086</td>\n",
       "      <td>0.188240</td>\n",
       "      <td>0.052609</td>\n",
       "      <td>0.085935</td>\n",
       "      <td>0.111702</td>\n",
       "      <td>0.132942</td>\n",
       "      <td>0.050221</td>\n",
       "      <td>0.061406</td>\n",
       "      <td>0.066760</td>\n",
       "      <td>0.058355</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.011946</td>\n",
       "      <td>0.089825</td>\n",
       "      <td>0.021788</td>\n",
       "      <td>0.127285</td>\n",
       "      <td>0.224942</td>\n",
       "      <td>0.185015</td>\n",
       "      <td>0.099188</td>\n",
       "      <td>0.133363</td>\n",
       "      <td>0.110034</td>\n",
       "      <td>0.079512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RAPT4.SA</th>\n",
       "      <td>0.454932</td>\n",
       "      <td>0.211906</td>\n",
       "      <td>0.380413</td>\n",
       "      <td>0.530011</td>\n",
       "      <td>0.511605</td>\n",
       "      <td>0.484169</td>\n",
       "      <td>0.486974</td>\n",
       "      <td>0.517438</td>\n",
       "      <td>0.560616</td>\n",
       "      <td>0.583196</td>\n",
       "      <td>...</td>\n",
       "      <td>0.343339</td>\n",
       "      <td>0.531858</td>\n",
       "      <td>0.308392</td>\n",
       "      <td>0.508945</td>\n",
       "      <td>0.513537</td>\n",
       "      <td>0.253348</td>\n",
       "      <td>0.520400</td>\n",
       "      <td>0.498992</td>\n",
       "      <td>0.374031</td>\n",
       "      <td>0.600619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RCSL4.SA</th>\n",
       "      <td>0.281580</td>\n",
       "      <td>0.155771</td>\n",
       "      <td>0.152560</td>\n",
       "      <td>0.213612</td>\n",
       "      <td>0.255403</td>\n",
       "      <td>0.207330</td>\n",
       "      <td>0.253934</td>\n",
       "      <td>0.287159</td>\n",
       "      <td>0.262100</td>\n",
       "      <td>0.272815</td>\n",
       "      <td>...</td>\n",
       "      <td>0.193773</td>\n",
       "      <td>0.263072</td>\n",
       "      <td>0.082180</td>\n",
       "      <td>0.230166</td>\n",
       "      <td>0.236700</td>\n",
       "      <td>0.161276</td>\n",
       "      <td>0.216857</td>\n",
       "      <td>0.283134</td>\n",
       "      <td>0.189366</td>\n",
       "      <td>0.226100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RENT3.SA</th>\n",
       "      <td>0.364446</td>\n",
       "      <td>0.250369</td>\n",
       "      <td>0.450874</td>\n",
       "      <td>0.518658</td>\n",
       "      <td>0.438981</td>\n",
       "      <td>0.408503</td>\n",
       "      <td>0.487505</td>\n",
       "      <td>0.529351</td>\n",
       "      <td>0.468737</td>\n",
       "      <td>0.473025</td>\n",
       "      <td>...</td>\n",
       "      <td>0.414309</td>\n",
       "      <td>0.512460</td>\n",
       "      <td>0.311516</td>\n",
       "      <td>0.510909</td>\n",
       "      <td>0.300624</td>\n",
       "      <td>0.218849</td>\n",
       "      <td>0.498760</td>\n",
       "      <td>0.375596</td>\n",
       "      <td>0.359664</td>\n",
       "      <td>0.458572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SANB11.SA</th>\n",
       "      <td>0.592440</td>\n",
       "      <td>0.212915</td>\n",
       "      <td>0.300327</td>\n",
       "      <td>0.580026</td>\n",
       "      <td>0.406556</td>\n",
       "      <td>0.356641</td>\n",
       "      <td>0.558028</td>\n",
       "      <td>0.460383</td>\n",
       "      <td>0.812630</td>\n",
       "      <td>0.875324</td>\n",
       "      <td>...</td>\n",
       "      <td>0.161989</td>\n",
       "      <td>0.498394</td>\n",
       "      <td>0.344798</td>\n",
       "      <td>0.518260</td>\n",
       "      <td>0.393381</td>\n",
       "      <td>0.375394</td>\n",
       "      <td>0.537826</td>\n",
       "      <td>0.331459</td>\n",
       "      <td>0.233126</td>\n",
       "      <td>0.470607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SAPR11.SA</th>\n",
       "      <td>0.433342</td>\n",
       "      <td>0.174882</td>\n",
       "      <td>0.273747</td>\n",
       "      <td>0.528922</td>\n",
       "      <td>0.497052</td>\n",
       "      <td>0.416056</td>\n",
       "      <td>0.387707</td>\n",
       "      <td>0.488204</td>\n",
       "      <td>0.510273</td>\n",
       "      <td>0.524353</td>\n",
       "      <td>...</td>\n",
       "      <td>0.373725</td>\n",
       "      <td>0.509252</td>\n",
       "      <td>0.322324</td>\n",
       "      <td>0.452017</td>\n",
       "      <td>0.316767</td>\n",
       "      <td>0.103251</td>\n",
       "      <td>0.482316</td>\n",
       "      <td>0.465503</td>\n",
       "      <td>0.277473</td>\n",
       "      <td>0.500792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SAPR4.SA</th>\n",
       "      <td>0.438932</td>\n",
       "      <td>0.230370</td>\n",
       "      <td>0.268793</td>\n",
       "      <td>0.532011</td>\n",
       "      <td>0.465370</td>\n",
       "      <td>0.422360</td>\n",
       "      <td>0.412018</td>\n",
       "      <td>0.509385</td>\n",
       "      <td>0.491739</td>\n",
       "      <td>0.503627</td>\n",
       "      <td>...</td>\n",
       "      <td>0.417910</td>\n",
       "      <td>0.513698</td>\n",
       "      <td>0.316213</td>\n",
       "      <td>0.475950</td>\n",
       "      <td>0.340800</td>\n",
       "      <td>0.121380</td>\n",
       "      <td>0.445412</td>\n",
       "      <td>0.468813</td>\n",
       "      <td>0.301516</td>\n",
       "      <td>0.510340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SBSP3.SA</th>\n",
       "      <td>0.470622</td>\n",
       "      <td>0.093933</td>\n",
       "      <td>0.279634</td>\n",
       "      <td>0.513619</td>\n",
       "      <td>0.491562</td>\n",
       "      <td>0.346380</td>\n",
       "      <td>0.392489</td>\n",
       "      <td>0.537634</td>\n",
       "      <td>0.577245</td>\n",
       "      <td>0.569382</td>\n",
       "      <td>...</td>\n",
       "      <td>0.380230</td>\n",
       "      <td>0.507990</td>\n",
       "      <td>0.388185</td>\n",
       "      <td>0.505454</td>\n",
       "      <td>0.268750</td>\n",
       "      <td>0.130041</td>\n",
       "      <td>0.478155</td>\n",
       "      <td>0.497509</td>\n",
       "      <td>0.325338</td>\n",
       "      <td>0.453796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SEER3.SA</th>\n",
       "      <td>0.407979</td>\n",
       "      <td>0.231178</td>\n",
       "      <td>0.327230</td>\n",
       "      <td>0.534278</td>\n",
       "      <td>0.488009</td>\n",
       "      <td>0.578377</td>\n",
       "      <td>0.466970</td>\n",
       "      <td>0.487331</td>\n",
       "      <td>0.479049</td>\n",
       "      <td>0.478238</td>\n",
       "      <td>...</td>\n",
       "      <td>0.339612</td>\n",
       "      <td>0.512772</td>\n",
       "      <td>0.264467</td>\n",
       "      <td>0.430496</td>\n",
       "      <td>0.267703</td>\n",
       "      <td>0.037981</td>\n",
       "      <td>0.376264</td>\n",
       "      <td>0.343970</td>\n",
       "      <td>0.267326</td>\n",
       "      <td>0.659407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SLCE3.SA</th>\n",
       "      <td>0.110903</td>\n",
       "      <td>0.204980</td>\n",
       "      <td>0.121647</td>\n",
       "      <td>-0.006808</td>\n",
       "      <td>0.056998</td>\n",
       "      <td>0.099124</td>\n",
       "      <td>-0.057007</td>\n",
       "      <td>0.135110</td>\n",
       "      <td>0.067682</td>\n",
       "      <td>-0.011633</td>\n",
       "      <td>...</td>\n",
       "      <td>0.239949</td>\n",
       "      <td>0.070244</td>\n",
       "      <td>0.074609</td>\n",
       "      <td>0.126320</td>\n",
       "      <td>0.133689</td>\n",
       "      <td>0.116820</td>\n",
       "      <td>0.062852</td>\n",
       "      <td>0.211627</td>\n",
       "      <td>0.231968</td>\n",
       "      <td>0.095573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SMLS3.SA</th>\n",
       "      <td>0.426584</td>\n",
       "      <td>0.207714</td>\n",
       "      <td>0.236446</td>\n",
       "      <td>0.550800</td>\n",
       "      <td>0.538038</td>\n",
       "      <td>0.392396</td>\n",
       "      <td>0.597054</td>\n",
       "      <td>0.378885</td>\n",
       "      <td>0.557480</td>\n",
       "      <td>0.524882</td>\n",
       "      <td>...</td>\n",
       "      <td>0.226806</td>\n",
       "      <td>0.575096</td>\n",
       "      <td>0.153150</td>\n",
       "      <td>0.399075</td>\n",
       "      <td>0.297783</td>\n",
       "      <td>0.097616</td>\n",
       "      <td>0.454402</td>\n",
       "      <td>0.395200</td>\n",
       "      <td>0.176703</td>\n",
       "      <td>0.550257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SMTO3.SA</th>\n",
       "      <td>0.356144</td>\n",
       "      <td>0.052273</td>\n",
       "      <td>0.238209</td>\n",
       "      <td>0.286942</td>\n",
       "      <td>0.245133</td>\n",
       "      <td>0.289559</td>\n",
       "      <td>0.279075</td>\n",
       "      <td>0.228967</td>\n",
       "      <td>0.305975</td>\n",
       "      <td>0.284292</td>\n",
       "      <td>...</td>\n",
       "      <td>0.248362</td>\n",
       "      <td>0.237053</td>\n",
       "      <td>0.311627</td>\n",
       "      <td>0.324718</td>\n",
       "      <td>0.288475</td>\n",
       "      <td>0.204747</td>\n",
       "      <td>0.328858</td>\n",
       "      <td>0.235091</td>\n",
       "      <td>0.316978</td>\n",
       "      <td>0.289425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SOMA3.SA</th>\n",
       "      <td>0.260279</td>\n",
       "      <td>0.237658</td>\n",
       "      <td>0.180095</td>\n",
       "      <td>0.317071</td>\n",
       "      <td>0.364808</td>\n",
       "      <td>0.259271</td>\n",
       "      <td>0.289188</td>\n",
       "      <td>0.198186</td>\n",
       "      <td>0.313673</td>\n",
       "      <td>0.320258</td>\n",
       "      <td>...</td>\n",
       "      <td>0.135938</td>\n",
       "      <td>0.354805</td>\n",
       "      <td>0.164957</td>\n",
       "      <td>0.262975</td>\n",
       "      <td>0.055949</td>\n",
       "      <td>0.033620</td>\n",
       "      <td>0.271775</td>\n",
       "      <td>0.265641</td>\n",
       "      <td>0.105282</td>\n",
       "      <td>0.359911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STBP3.SA</th>\n",
       "      <td>0.309614</td>\n",
       "      <td>0.143408</td>\n",
       "      <td>0.367157</td>\n",
       "      <td>0.550350</td>\n",
       "      <td>0.533415</td>\n",
       "      <td>0.443265</td>\n",
       "      <td>0.459524</td>\n",
       "      <td>0.411633</td>\n",
       "      <td>0.398096</td>\n",
       "      <td>0.351618</td>\n",
       "      <td>...</td>\n",
       "      <td>0.313924</td>\n",
       "      <td>0.579944</td>\n",
       "      <td>0.208907</td>\n",
       "      <td>0.483163</td>\n",
       "      <td>0.287050</td>\n",
       "      <td>0.102143</td>\n",
       "      <td>0.415466</td>\n",
       "      <td>0.439847</td>\n",
       "      <td>0.256279</td>\n",
       "      <td>0.467947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUZB3.SA</th>\n",
       "      <td>0.031373</td>\n",
       "      <td>-0.027432</td>\n",
       "      <td>-0.032747</td>\n",
       "      <td>-0.165209</td>\n",
       "      <td>-0.279310</td>\n",
       "      <td>-0.108764</td>\n",
       "      <td>-0.201820</td>\n",
       "      <td>-0.113491</td>\n",
       "      <td>-0.167469</td>\n",
       "      <td>-0.121633</td>\n",
       "      <td>...</td>\n",
       "      <td>0.019946</td>\n",
       "      <td>-0.264552</td>\n",
       "      <td>-0.039697</td>\n",
       "      <td>-0.051065</td>\n",
       "      <td>0.094772</td>\n",
       "      <td>0.252158</td>\n",
       "      <td>-0.113793</td>\n",
       "      <td>-0.054291</td>\n",
       "      <td>0.059237</td>\n",
       "      <td>-0.178798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TAEE11.SA</th>\n",
       "      <td>0.343070</td>\n",
       "      <td>0.061481</td>\n",
       "      <td>0.298015</td>\n",
       "      <td>0.360287</td>\n",
       "      <td>0.252319</td>\n",
       "      <td>0.291438</td>\n",
       "      <td>0.271806</td>\n",
       "      <td>0.369745</td>\n",
       "      <td>0.348178</td>\n",
       "      <td>0.351519</td>\n",
       "      <td>...</td>\n",
       "      <td>0.284861</td>\n",
       "      <td>0.277411</td>\n",
       "      <td>0.571860</td>\n",
       "      <td>0.411607</td>\n",
       "      <td>0.096448</td>\n",
       "      <td>-0.051599</td>\n",
       "      <td>0.366730</td>\n",
       "      <td>0.316670</td>\n",
       "      <td>0.229367</td>\n",
       "      <td>0.271656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TASA4.SA</th>\n",
       "      <td>0.145486</td>\n",
       "      <td>-0.054997</td>\n",
       "      <td>0.085942</td>\n",
       "      <td>0.044743</td>\n",
       "      <td>0.004492</td>\n",
       "      <td>0.138332</td>\n",
       "      <td>0.051235</td>\n",
       "      <td>0.095170</td>\n",
       "      <td>0.080570</td>\n",
       "      <td>0.049041</td>\n",
       "      <td>...</td>\n",
       "      <td>0.120990</td>\n",
       "      <td>0.049753</td>\n",
       "      <td>0.012147</td>\n",
       "      <td>0.037623</td>\n",
       "      <td>0.174606</td>\n",
       "      <td>0.074196</td>\n",
       "      <td>0.034599</td>\n",
       "      <td>0.141142</td>\n",
       "      <td>0.054589</td>\n",
       "      <td>0.086691</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TCSA3.SA</th>\n",
       "      <td>0.379048</td>\n",
       "      <td>0.143758</td>\n",
       "      <td>0.438381</td>\n",
       "      <td>0.523705</td>\n",
       "      <td>0.555786</td>\n",
       "      <td>0.474952</td>\n",
       "      <td>0.499651</td>\n",
       "      <td>0.466982</td>\n",
       "      <td>0.459144</td>\n",
       "      <td>0.435270</td>\n",
       "      <td>...</td>\n",
       "      <td>0.298003</td>\n",
       "      <td>0.606394</td>\n",
       "      <td>0.252786</td>\n",
       "      <td>0.438931</td>\n",
       "      <td>0.351776</td>\n",
       "      <td>0.114005</td>\n",
       "      <td>0.454376</td>\n",
       "      <td>0.471911</td>\n",
       "      <td>0.277392</td>\n",
       "      <td>0.519719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TEND3.SA</th>\n",
       "      <td>0.445134</td>\n",
       "      <td>0.222460</td>\n",
       "      <td>0.545736</td>\n",
       "      <td>0.612819</td>\n",
       "      <td>0.619040</td>\n",
       "      <td>0.587503</td>\n",
       "      <td>0.488044</td>\n",
       "      <td>0.593971</td>\n",
       "      <td>0.517661</td>\n",
       "      <td>0.524514</td>\n",
       "      <td>...</td>\n",
       "      <td>0.437644</td>\n",
       "      <td>0.716865</td>\n",
       "      <td>0.391212</td>\n",
       "      <td>0.501198</td>\n",
       "      <td>0.342529</td>\n",
       "      <td>0.117657</td>\n",
       "      <td>0.633945</td>\n",
       "      <td>0.504702</td>\n",
       "      <td>0.346142</td>\n",
       "      <td>0.586186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TIET11.SA</th>\n",
       "      <td>0.285892</td>\n",
       "      <td>0.074750</td>\n",
       "      <td>0.303300</td>\n",
       "      <td>0.272134</td>\n",
       "      <td>0.182888</td>\n",
       "      <td>0.276129</td>\n",
       "      <td>0.253083</td>\n",
       "      <td>0.341408</td>\n",
       "      <td>0.382519</td>\n",
       "      <td>0.352547</td>\n",
       "      <td>...</td>\n",
       "      <td>0.293094</td>\n",
       "      <td>0.314527</td>\n",
       "      <td>0.341748</td>\n",
       "      <td>0.296197</td>\n",
       "      <td>0.210296</td>\n",
       "      <td>0.064959</td>\n",
       "      <td>0.276630</td>\n",
       "      <td>0.272833</td>\n",
       "      <td>0.208563</td>\n",
       "      <td>0.213961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TOTS3.SA</th>\n",
       "      <td>0.250331</td>\n",
       "      <td>0.037322</td>\n",
       "      <td>0.337021</td>\n",
       "      <td>0.365894</td>\n",
       "      <td>0.330376</td>\n",
       "      <td>0.371036</td>\n",
       "      <td>0.225213</td>\n",
       "      <td>0.492184</td>\n",
       "      <td>0.300798</td>\n",
       "      <td>0.234106</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.386895</td>\n",
       "      <td>0.243379</td>\n",
       "      <td>0.375015</td>\n",
       "      <td>0.163519</td>\n",
       "      <td>0.014472</td>\n",
       "      <td>0.359768</td>\n",
       "      <td>0.419108</td>\n",
       "      <td>0.452858</td>\n",
       "      <td>0.323290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TRIS3.SA</th>\n",
       "      <td>0.376912</td>\n",
       "      <td>0.185700</td>\n",
       "      <td>0.418931</td>\n",
       "      <td>0.658830</td>\n",
       "      <td>0.709588</td>\n",
       "      <td>0.490145</td>\n",
       "      <td>0.514326</td>\n",
       "      <td>0.536870</td>\n",
       "      <td>0.566172</td>\n",
       "      <td>0.510220</td>\n",
       "      <td>...</td>\n",
       "      <td>0.386895</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.269964</td>\n",
       "      <td>0.500333</td>\n",
       "      <td>0.262653</td>\n",
       "      <td>0.044899</td>\n",
       "      <td>0.556502</td>\n",
       "      <td>0.491051</td>\n",
       "      <td>0.265609</td>\n",
       "      <td>0.585905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TRPL4.SA</th>\n",
       "      <td>0.317283</td>\n",
       "      <td>0.225195</td>\n",
       "      <td>0.319789</td>\n",
       "      <td>0.340378</td>\n",
       "      <td>0.190449</td>\n",
       "      <td>0.260704</td>\n",
       "      <td>0.291341</td>\n",
       "      <td>0.341926</td>\n",
       "      <td>0.394337</td>\n",
       "      <td>0.384304</td>\n",
       "      <td>...</td>\n",
       "      <td>0.243379</td>\n",
       "      <td>0.269964</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.375097</td>\n",
       "      <td>0.236252</td>\n",
       "      <td>0.066405</td>\n",
       "      <td>0.355229</td>\n",
       "      <td>0.276657</td>\n",
       "      <td>0.237594</td>\n",
       "      <td>0.239877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UGPA3.SA</th>\n",
       "      <td>0.494798</td>\n",
       "      <td>0.256135</td>\n",
       "      <td>0.379642</td>\n",
       "      <td>0.550140</td>\n",
       "      <td>0.435800</td>\n",
       "      <td>0.373479</td>\n",
       "      <td>0.439771</td>\n",
       "      <td>0.495214</td>\n",
       "      <td>0.582971</td>\n",
       "      <td>0.594559</td>\n",
       "      <td>...</td>\n",
       "      <td>0.375015</td>\n",
       "      <td>0.500333</td>\n",
       "      <td>0.375097</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.362609</td>\n",
       "      <td>0.254255</td>\n",
       "      <td>0.461088</td>\n",
       "      <td>0.392243</td>\n",
       "      <td>0.250840</td>\n",
       "      <td>0.471220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>USIM5.SA</th>\n",
       "      <td>0.319783</td>\n",
       "      <td>0.096066</td>\n",
       "      <td>0.216358</td>\n",
       "      <td>0.236166</td>\n",
       "      <td>0.273988</td>\n",
       "      <td>0.285327</td>\n",
       "      <td>0.372027</td>\n",
       "      <td>0.320611</td>\n",
       "      <td>0.418089</td>\n",
       "      <td>0.420055</td>\n",
       "      <td>...</td>\n",
       "      <td>0.163519</td>\n",
       "      <td>0.262653</td>\n",
       "      <td>0.236252</td>\n",
       "      <td>0.362609</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.512691</td>\n",
       "      <td>0.313981</td>\n",
       "      <td>0.317109</td>\n",
       "      <td>0.255131</td>\n",
       "      <td>0.289774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VALE3.SA</th>\n",
       "      <td>0.220859</td>\n",
       "      <td>0.007395</td>\n",
       "      <td>0.055889</td>\n",
       "      <td>0.149611</td>\n",
       "      <td>0.032308</td>\n",
       "      <td>0.064754</td>\n",
       "      <td>0.169001</td>\n",
       "      <td>0.212417</td>\n",
       "      <td>0.304232</td>\n",
       "      <td>0.361119</td>\n",
       "      <td>...</td>\n",
       "      <td>0.014472</td>\n",
       "      <td>0.044899</td>\n",
       "      <td>0.066405</td>\n",
       "      <td>0.254255</td>\n",
       "      <td>0.512691</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.173186</td>\n",
       "      <td>0.055837</td>\n",
       "      <td>0.157493</td>\n",
       "      <td>0.138029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VIVA3.SA</th>\n",
       "      <td>0.471905</td>\n",
       "      <td>0.147076</td>\n",
       "      <td>0.486406</td>\n",
       "      <td>0.558100</td>\n",
       "      <td>0.592988</td>\n",
       "      <td>0.429799</td>\n",
       "      <td>0.486329</td>\n",
       "      <td>0.498249</td>\n",
       "      <td>0.492367</td>\n",
       "      <td>0.535364</td>\n",
       "      <td>...</td>\n",
       "      <td>0.359768</td>\n",
       "      <td>0.556502</td>\n",
       "      <td>0.355229</td>\n",
       "      <td>0.461088</td>\n",
       "      <td>0.313981</td>\n",
       "      <td>0.173186</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.456129</td>\n",
       "      <td>0.328878</td>\n",
       "      <td>0.537041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VVAR3.SA</th>\n",
       "      <td>0.253505</td>\n",
       "      <td>0.237632</td>\n",
       "      <td>0.284553</td>\n",
       "      <td>0.443484</td>\n",
       "      <td>0.490582</td>\n",
       "      <td>0.387079</td>\n",
       "      <td>0.367273</td>\n",
       "      <td>0.475400</td>\n",
       "      <td>0.484123</td>\n",
       "      <td>0.376597</td>\n",
       "      <td>...</td>\n",
       "      <td>0.419108</td>\n",
       "      <td>0.491051</td>\n",
       "      <td>0.276657</td>\n",
       "      <td>0.392243</td>\n",
       "      <td>0.317109</td>\n",
       "      <td>0.055837</td>\n",
       "      <td>0.456129</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.358932</td>\n",
       "      <td>0.344747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WEGE3.SA</th>\n",
       "      <td>0.337792</td>\n",
       "      <td>0.193966</td>\n",
       "      <td>0.353214</td>\n",
       "      <td>0.230735</td>\n",
       "      <td>0.263656</td>\n",
       "      <td>0.295470</td>\n",
       "      <td>0.184805</td>\n",
       "      <td>0.462275</td>\n",
       "      <td>0.280515</td>\n",
       "      <td>0.269855</td>\n",
       "      <td>...</td>\n",
       "      <td>0.452858</td>\n",
       "      <td>0.265609</td>\n",
       "      <td>0.237594</td>\n",
       "      <td>0.250840</td>\n",
       "      <td>0.255131</td>\n",
       "      <td>0.157493</td>\n",
       "      <td>0.328878</td>\n",
       "      <td>0.358932</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.282602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YDUQ3.SA</th>\n",
       "      <td>0.471294</td>\n",
       "      <td>0.218626</td>\n",
       "      <td>0.384966</td>\n",
       "      <td>0.549408</td>\n",
       "      <td>0.618716</td>\n",
       "      <td>0.534941</td>\n",
       "      <td>0.494654</td>\n",
       "      <td>0.449871</td>\n",
       "      <td>0.475466</td>\n",
       "      <td>0.492510</td>\n",
       "      <td>...</td>\n",
       "      <td>0.323290</td>\n",
       "      <td>0.585905</td>\n",
       "      <td>0.239877</td>\n",
       "      <td>0.471220</td>\n",
       "      <td>0.289774</td>\n",
       "      <td>0.138029</td>\n",
       "      <td>0.537041</td>\n",
       "      <td>0.344747</td>\n",
       "      <td>0.282602</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 150 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           ABEV3.SA  AERI3.SA  ALPA4.SA  ALSO3.SA  AMAR3.SA  ANIM3.SA  \\\n",
       "ABEV3.SA   1.000000  0.130357  0.283051  0.425000  0.346233  0.310454   \n",
       "AERI3.SA   0.130357  1.000000  0.177212  0.168305  0.223260  0.114943   \n",
       "ALPA4.SA   0.283051  0.177212  1.000000  0.436558  0.407595  0.423060   \n",
       "ALSO3.SA   0.425000  0.168305  0.436558  1.000000  0.592428  0.461950   \n",
       "AMAR3.SA   0.346233  0.223260  0.407595  0.592428  1.000000  0.508808   \n",
       "ANIM3.SA   0.310454  0.114943  0.423060  0.461950  0.508808  1.000000   \n",
       "AZUL4.SA   0.402720  0.274572  0.329780  0.589075  0.480475  0.344041   \n",
       "B3SA3.SA   0.424210  0.214604  0.424040  0.495238  0.427833  0.396803   \n",
       "BBAS3.SA   0.568497  0.191074  0.325419  0.607750  0.476953  0.390703   \n",
       "BBDC3.SA   0.624730  0.218975  0.326771  0.628556  0.444859  0.375097   \n",
       "BBDC4.SA   0.642411  0.212805  0.309654  0.612613  0.429129  0.344736   \n",
       "BBSE3.SA   0.489181  0.226997  0.394964  0.528830  0.560273  0.452708   \n",
       "BEEF3.SA   0.116238  0.123551  0.047214  0.043556 -0.059209  0.054806   \n",
       "BIDI4.SA   0.267361  0.194437  0.214704  0.285123  0.271282  0.257797   \n",
       "BKBR3.SA   0.350399  0.255859  0.234580  0.450903  0.547001  0.424125   \n",
       "BMGB4.SA   0.405669  0.130594  0.268647  0.472417  0.508713  0.311234   \n",
       "BPAC11.SA  0.347235  0.217739  0.469102  0.567655  0.513351  0.358054   \n",
       "BPAN4.SA  -0.064777 -0.052091  0.003605  0.051187  0.076989  0.072805   \n",
       "BRAP4.SA   0.231836  0.019969  0.099214  0.146265  0.023511  0.085884   \n",
       "BRDT3.SA   0.527924  0.087028  0.449752  0.622095  0.524699  0.389427   \n",
       "BRFS3.SA   0.270158  0.169293  0.098508  0.286966  0.067618  0.178562   \n",
       "BRKM5.SA   0.330664  0.085338  0.245153  0.213484  0.166790  0.246415   \n",
       "BRML3.SA   0.439156  0.085328  0.376454  0.879162  0.576875  0.441785   \n",
       "BRPR3.SA   0.476427  0.144513  0.364461  0.727617  0.536390  0.411086   \n",
       "BRSR6.SA   0.520014  0.288650  0.249216  0.544614  0.513564  0.385575   \n",
       "BTOW3.SA   0.210269  0.279530  0.261045  0.275801  0.192967  0.283450   \n",
       "CAML3.SA   0.287550  0.228125  0.278213  0.330043  0.254254  0.330328   \n",
       "CASH3.SA   0.123295  0.329927  0.340290  0.169034  0.233588  0.155630   \n",
       "CCRO3.SA   0.422174  0.240019  0.393796  0.594058  0.527209  0.350284   \n",
       "CEAB3.SA   0.381106  0.167113  0.390066  0.573841  0.626454  0.469403   \n",
       "...             ...       ...       ...       ...       ...       ...   \n",
       "RANI3.SA  -0.012086  0.188240  0.052609  0.085935  0.111702  0.132942   \n",
       "RAPT4.SA   0.454932  0.211906  0.380413  0.530011  0.511605  0.484169   \n",
       "RCSL4.SA   0.281580  0.155771  0.152560  0.213612  0.255403  0.207330   \n",
       "RENT3.SA   0.364446  0.250369  0.450874  0.518658  0.438981  0.408503   \n",
       "SANB11.SA  0.592440  0.212915  0.300327  0.580026  0.406556  0.356641   \n",
       "SAPR11.SA  0.433342  0.174882  0.273747  0.528922  0.497052  0.416056   \n",
       "SAPR4.SA   0.438932  0.230370  0.268793  0.532011  0.465370  0.422360   \n",
       "SBSP3.SA   0.470622  0.093933  0.279634  0.513619  0.491562  0.346380   \n",
       "SEER3.SA   0.407979  0.231178  0.327230  0.534278  0.488009  0.578377   \n",
       "SLCE3.SA   0.110903  0.204980  0.121647 -0.006808  0.056998  0.099124   \n",
       "SMLS3.SA   0.426584  0.207714  0.236446  0.550800  0.538038  0.392396   \n",
       "SMTO3.SA   0.356144  0.052273  0.238209  0.286942  0.245133  0.289559   \n",
       "SOMA3.SA   0.260279  0.237658  0.180095  0.317071  0.364808  0.259271   \n",
       "STBP3.SA   0.309614  0.143408  0.367157  0.550350  0.533415  0.443265   \n",
       "SUZB3.SA   0.031373 -0.027432 -0.032747 -0.165209 -0.279310 -0.108764   \n",
       "TAEE11.SA  0.343070  0.061481  0.298015  0.360287  0.252319  0.291438   \n",
       "TASA4.SA   0.145486 -0.054997  0.085942  0.044743  0.004492  0.138332   \n",
       "TCSA3.SA   0.379048  0.143758  0.438381  0.523705  0.555786  0.474952   \n",
       "TEND3.SA   0.445134  0.222460  0.545736  0.612819  0.619040  0.587503   \n",
       "TIET11.SA  0.285892  0.074750  0.303300  0.272134  0.182888  0.276129   \n",
       "TOTS3.SA   0.250331  0.037322  0.337021  0.365894  0.330376  0.371036   \n",
       "TRIS3.SA   0.376912  0.185700  0.418931  0.658830  0.709588  0.490145   \n",
       "TRPL4.SA   0.317283  0.225195  0.319789  0.340378  0.190449  0.260704   \n",
       "UGPA3.SA   0.494798  0.256135  0.379642  0.550140  0.435800  0.373479   \n",
       "USIM5.SA   0.319783  0.096066  0.216358  0.236166  0.273988  0.285327   \n",
       "VALE3.SA   0.220859  0.007395  0.055889  0.149611  0.032308  0.064754   \n",
       "VIVA3.SA   0.471905  0.147076  0.486406  0.558100  0.592988  0.429799   \n",
       "VVAR3.SA   0.253505  0.237632  0.284553  0.443484  0.490582  0.387079   \n",
       "WEGE3.SA   0.337792  0.193966  0.353214  0.230735  0.263656  0.295470   \n",
       "YDUQ3.SA   0.471294  0.218626  0.384966  0.549408  0.618716  0.534941   \n",
       "\n",
       "           AZUL4.SA  B3SA3.SA  BBAS3.SA  BBDC3.SA  ...  TOTS3.SA  TRIS3.SA  \\\n",
       "ABEV3.SA   0.402720  0.424210  0.568497  0.624730  ...  0.250331  0.376912   \n",
       "AERI3.SA   0.274572  0.214604  0.191074  0.218975  ...  0.037322  0.185700   \n",
       "ALPA4.SA   0.329780  0.424040  0.325419  0.326771  ...  0.337021  0.418931   \n",
       "ALSO3.SA   0.589075  0.495238  0.607750  0.628556  ...  0.365894  0.658830   \n",
       "AMAR3.SA   0.480475  0.427833  0.476953  0.444859  ...  0.330376  0.709588   \n",
       "ANIM3.SA   0.344041  0.396803  0.390703  0.375097  ...  0.371036  0.490145   \n",
       "AZUL4.SA   1.000000  0.381688  0.563973  0.573759  ...  0.225213  0.514326   \n",
       "B3SA3.SA   0.381688  1.000000  0.546217  0.533654  ...  0.492184  0.536870   \n",
       "BBAS3.SA   0.563973  0.546217  1.000000  0.892512  ...  0.300798  0.566172   \n",
       "BBDC3.SA   0.573759  0.533654  0.892512  1.000000  ...  0.234106  0.510220   \n",
       "BBDC4.SA   0.576639  0.491570  0.876182  0.970756  ...  0.179817  0.478835   \n",
       "BBSE3.SA   0.440024  0.538062  0.608050  0.610447  ...  0.417267  0.572240   \n",
       "BEEF3.SA  -0.095907  0.129839  0.074578  0.058067  ...  0.114514 -0.106063   \n",
       "BIDI4.SA   0.197584  0.307090  0.242458  0.203714  ...  0.350452  0.349461   \n",
       "BKBR3.SA   0.435047  0.369288  0.379855  0.349280  ...  0.297177  0.483587   \n",
       "BMGB4.SA   0.422801  0.388643  0.508576  0.507922  ...  0.262823  0.538495   \n",
       "BPAC11.SA  0.497027  0.625072  0.549920  0.536951  ...  0.446725  0.630288   \n",
       "BPAN4.SA   0.006770 -0.026151 -0.167320 -0.058150  ... -0.095737  0.098609   \n",
       "BRAP4.SA   0.158613  0.231783  0.272145  0.325777  ...  0.074007  0.059414   \n",
       "BRDT3.SA   0.467207  0.583560  0.659330  0.657639  ...  0.436375  0.579869   \n",
       "BRFS3.SA   0.190293  0.208612  0.349708  0.335743  ...  0.251088  0.088448   \n",
       "BRKM5.SA   0.293355  0.294789  0.339461  0.366027  ...  0.197415  0.204558   \n",
       "BRML3.SA   0.614909  0.514477  0.602402  0.617651  ...  0.367369  0.635251   \n",
       "BRPR3.SA   0.582699  0.459528  0.529902  0.538350  ...  0.350813  0.581471   \n",
       "BRSR6.SA   0.528392  0.460483  0.731650  0.765500  ...  0.257249  0.523723   \n",
       "BTOW3.SA   0.141325  0.324521  0.165910  0.132757  ...  0.415645  0.234886   \n",
       "CAML3.SA   0.149942  0.384746  0.286401  0.295661  ...  0.374057  0.249878   \n",
       "CASH3.SA   0.237897  0.185601  0.168435  0.063781  ...  0.185417  0.185198   \n",
       "CCRO3.SA   0.495258  0.592153  0.608991  0.603977  ...  0.339438  0.574684   \n",
       "CEAB3.SA   0.540569  0.379141  0.477003  0.508402  ...  0.368862  0.569818   \n",
       "...             ...       ...       ...       ...  ...       ...       ...   \n",
       "RANI3.SA   0.050221  0.061406  0.066760  0.058355  ... -0.011946  0.089825   \n",
       "RAPT4.SA   0.486974  0.517438  0.560616  0.583196  ...  0.343339  0.531858   \n",
       "RCSL4.SA   0.253934  0.287159  0.262100  0.272815  ...  0.193773  0.263072   \n",
       "RENT3.SA   0.487505  0.529351  0.468737  0.473025  ...  0.414309  0.512460   \n",
       "SANB11.SA  0.558028  0.460383  0.812630  0.875324  ...  0.161989  0.498394   \n",
       "SAPR11.SA  0.387707  0.488204  0.510273  0.524353  ...  0.373725  0.509252   \n",
       "SAPR4.SA   0.412018  0.509385  0.491739  0.503627  ...  0.417910  0.513698   \n",
       "SBSP3.SA   0.392489  0.537634  0.577245  0.569382  ...  0.380230  0.507990   \n",
       "SEER3.SA   0.466970  0.487331  0.479049  0.478238  ...  0.339612  0.512772   \n",
       "SLCE3.SA  -0.057007  0.135110  0.067682 -0.011633  ...  0.239949  0.070244   \n",
       "SMLS3.SA   0.597054  0.378885  0.557480  0.524882  ...  0.226806  0.575096   \n",
       "SMTO3.SA   0.279075  0.228967  0.305975  0.284292  ...  0.248362  0.237053   \n",
       "SOMA3.SA   0.289188  0.198186  0.313673  0.320258  ...  0.135938  0.354805   \n",
       "STBP3.SA   0.459524  0.411633  0.398096  0.351618  ...  0.313924  0.579944   \n",
       "SUZB3.SA  -0.201820 -0.113491 -0.167469 -0.121633  ...  0.019946 -0.264552   \n",
       "TAEE11.SA  0.271806  0.369745  0.348178  0.351519  ...  0.284861  0.277411   \n",
       "TASA4.SA   0.051235  0.095170  0.080570  0.049041  ...  0.120990  0.049753   \n",
       "TCSA3.SA   0.499651  0.466982  0.459144  0.435270  ...  0.298003  0.606394   \n",
       "TEND3.SA   0.488044  0.593971  0.517661  0.524514  ...  0.437644  0.716865   \n",
       "TIET11.SA  0.253083  0.341408  0.382519  0.352547  ...  0.293094  0.314527   \n",
       "TOTS3.SA   0.225213  0.492184  0.300798  0.234106  ...  1.000000  0.386895   \n",
       "TRIS3.SA   0.514326  0.536870  0.566172  0.510220  ...  0.386895  1.000000   \n",
       "TRPL4.SA   0.291341  0.341926  0.394337  0.384304  ...  0.243379  0.269964   \n",
       "UGPA3.SA   0.439771  0.495214  0.582971  0.594559  ...  0.375015  0.500333   \n",
       "USIM5.SA   0.372027  0.320611  0.418089  0.420055  ...  0.163519  0.262653   \n",
       "VALE3.SA   0.169001  0.212417  0.304232  0.361119  ...  0.014472  0.044899   \n",
       "VIVA3.SA   0.486329  0.498249  0.492367  0.535364  ...  0.359768  0.556502   \n",
       "VVAR3.SA   0.367273  0.475400  0.484123  0.376597  ...  0.419108  0.491051   \n",
       "WEGE3.SA   0.184805  0.462275  0.280515  0.269855  ...  0.452858  0.265609   \n",
       "YDUQ3.SA   0.494654  0.449871  0.475466  0.492510  ...  0.323290  0.585905   \n",
       "\n",
       "           TRPL4.SA  UGPA3.SA  USIM5.SA  VALE3.SA  VIVA3.SA  VVAR3.SA  \\\n",
       "ABEV3.SA   0.317283  0.494798  0.319783  0.220859  0.471905  0.253505   \n",
       "AERI3.SA   0.225195  0.256135  0.096066  0.007395  0.147076  0.237632   \n",
       "ALPA4.SA   0.319789  0.379642  0.216358  0.055889  0.486406  0.284553   \n",
       "ALSO3.SA   0.340378  0.550140  0.236166  0.149611  0.558100  0.443484   \n",
       "AMAR3.SA   0.190449  0.435800  0.273988  0.032308  0.592988  0.490582   \n",
       "ANIM3.SA   0.260704  0.373479  0.285327  0.064754  0.429799  0.387079   \n",
       "AZUL4.SA   0.291341  0.439771  0.372027  0.169001  0.486329  0.367273   \n",
       "B3SA3.SA   0.341926  0.495214  0.320611  0.212417  0.498249  0.475400   \n",
       "BBAS3.SA   0.394337  0.582971  0.418089  0.304232  0.492367  0.484123   \n",
       "BBDC3.SA   0.384304  0.594559  0.420055  0.361119  0.535364  0.376597   \n",
       "BBDC4.SA   0.370205  0.583470  0.405252  0.359996  0.512106  0.349123   \n",
       "BBSE3.SA   0.342205  0.546492  0.335124  0.198430  0.523842  0.440609   \n",
       "BEEF3.SA   0.143212  0.152114  0.072070  0.141695  0.021456  0.208817   \n",
       "BIDI4.SA   0.188540  0.213853  0.120762  0.057293  0.248729  0.381075   \n",
       "BKBR3.SA   0.243675  0.350253  0.302591  0.039182  0.435197  0.368263   \n",
       "BMGB4.SA   0.287214  0.402902  0.291914  0.112417  0.475470  0.335984   \n",
       "BPAC11.SA  0.318435  0.503464  0.308163  0.156336  0.562010  0.491691   \n",
       "BPAN4.SA  -0.108704 -0.018030  0.046383 -0.007375  0.048998 -0.042647   \n",
       "BRAP4.SA   0.140123  0.262200  0.497682  0.901751  0.170482  0.035451   \n",
       "BRDT3.SA   0.321044  0.706007  0.294432  0.220798  0.538563  0.457813   \n",
       "BRFS3.SA   0.267316  0.334911  0.151987  0.240274  0.196696  0.250501   \n",
       "BRKM5.SA   0.319444  0.318575  0.390667  0.212556  0.398119  0.332190   \n",
       "BRML3.SA   0.277585  0.532644  0.288941  0.141861  0.526896  0.459285   \n",
       "BRPR3.SA   0.270340  0.457412  0.294319  0.130236  0.512757  0.476062   \n",
       "BRSR6.SA   0.384218  0.538351  0.386693  0.263250  0.504362  0.397018   \n",
       "BTOW3.SA   0.169975  0.240747  0.111015  0.048684  0.232337  0.514076   \n",
       "CAML3.SA   0.229530  0.308516  0.228651  0.147389  0.224881  0.305848   \n",
       "CASH3.SA   0.250188  0.234508  0.156851  0.042035  0.176511  0.220557   \n",
       "CCRO3.SA   0.349060  0.590714  0.287641  0.193505  0.450750  0.391743   \n",
       "CEAB3.SA   0.249201  0.455648  0.315325  0.088981  0.540654  0.431328   \n",
       "...             ...       ...       ...       ...       ...       ...   \n",
       "RANI3.SA   0.021788  0.127285  0.224942  0.185015  0.099188  0.133363   \n",
       "RAPT4.SA   0.308392  0.508945  0.513537  0.253348  0.520400  0.498992   \n",
       "RCSL4.SA   0.082180  0.230166  0.236700  0.161276  0.216857  0.283134   \n",
       "RENT3.SA   0.311516  0.510909  0.300624  0.218849  0.498760  0.375596   \n",
       "SANB11.SA  0.344798  0.518260  0.393381  0.375394  0.537826  0.331459   \n",
       "SAPR11.SA  0.322324  0.452017  0.316767  0.103251  0.482316  0.465503   \n",
       "SAPR4.SA   0.316213  0.475950  0.340800  0.121380  0.445412  0.468813   \n",
       "SBSP3.SA   0.388185  0.505454  0.268750  0.130041  0.478155  0.497509   \n",
       "SEER3.SA   0.264467  0.430496  0.267703  0.037981  0.376264  0.343970   \n",
       "SLCE3.SA   0.074609  0.126320  0.133689  0.116820  0.062852  0.211627   \n",
       "SMLS3.SA   0.153150  0.399075  0.297783  0.097616  0.454402  0.395200   \n",
       "SMTO3.SA   0.311627  0.324718  0.288475  0.204747  0.328858  0.235091   \n",
       "SOMA3.SA   0.164957  0.262975  0.055949  0.033620  0.271775  0.265641   \n",
       "STBP3.SA   0.208907  0.483163  0.287050  0.102143  0.415466  0.439847   \n",
       "SUZB3.SA  -0.039697 -0.051065  0.094772  0.252158 -0.113793 -0.054291   \n",
       "TAEE11.SA  0.571860  0.411607  0.096448 -0.051599  0.366730  0.316670   \n",
       "TASA4.SA   0.012147  0.037623  0.174606  0.074196  0.034599  0.141142   \n",
       "TCSA3.SA   0.252786  0.438931  0.351776  0.114005  0.454376  0.471911   \n",
       "TEND3.SA   0.391212  0.501198  0.342529  0.117657  0.633945  0.504702   \n",
       "TIET11.SA  0.341748  0.296197  0.210296  0.064959  0.276630  0.272833   \n",
       "TOTS3.SA   0.243379  0.375015  0.163519  0.014472  0.359768  0.419108   \n",
       "TRIS3.SA   0.269964  0.500333  0.262653  0.044899  0.556502  0.491051   \n",
       "TRPL4.SA   1.000000  0.375097  0.236252  0.066405  0.355229  0.276657   \n",
       "UGPA3.SA   0.375097  1.000000  0.362609  0.254255  0.461088  0.392243   \n",
       "USIM5.SA   0.236252  0.362609  1.000000  0.512691  0.313981  0.317109   \n",
       "VALE3.SA   0.066405  0.254255  0.512691  1.000000  0.173186  0.055837   \n",
       "VIVA3.SA   0.355229  0.461088  0.313981  0.173186  1.000000  0.456129   \n",
       "VVAR3.SA   0.276657  0.392243  0.317109  0.055837  0.456129  1.000000   \n",
       "WEGE3.SA   0.237594  0.250840  0.255131  0.157493  0.328878  0.358932   \n",
       "YDUQ3.SA   0.239877  0.471220  0.289774  0.138029  0.537041  0.344747   \n",
       "\n",
       "           WEGE3.SA  YDUQ3.SA  \n",
       "ABEV3.SA   0.337792  0.471294  \n",
       "AERI3.SA   0.193966  0.218626  \n",
       "ALPA4.SA   0.353214  0.384966  \n",
       "ALSO3.SA   0.230735  0.549408  \n",
       "AMAR3.SA   0.263656  0.618716  \n",
       "ANIM3.SA   0.295470  0.534941  \n",
       "AZUL4.SA   0.184805  0.494654  \n",
       "B3SA3.SA   0.462275  0.449871  \n",
       "BBAS3.SA   0.280515  0.475466  \n",
       "BBDC3.SA   0.269855  0.492510  \n",
       "BBDC4.SA   0.216587  0.478712  \n",
       "BBSE3.SA   0.371867  0.555146  \n",
       "BEEF3.SA   0.132631 -0.019768  \n",
       "BIDI4.SA   0.343658  0.199483  \n",
       "BKBR3.SA   0.217056  0.381174  \n",
       "BMGB4.SA   0.208978  0.366185  \n",
       "BPAC11.SA  0.389276  0.485179  \n",
       "BPAN4.SA  -0.029522  0.001793  \n",
       "BRAP4.SA   0.243500  0.155792  \n",
       "BRDT3.SA   0.332309  0.551218  \n",
       "BRFS3.SA   0.152311  0.102571  \n",
       "BRKM5.SA   0.176952  0.253295  \n",
       "BRML3.SA   0.232413  0.533000  \n",
       "BRPR3.SA   0.298429  0.510320  \n",
       "BRSR6.SA   0.176333  0.514096  \n",
       "BTOW3.SA   0.398324  0.216062  \n",
       "CAML3.SA   0.309838  0.288093  \n",
       "CASH3.SA   0.255564  0.138597  \n",
       "CCRO3.SA   0.265839  0.478343  \n",
       "CEAB3.SA   0.283205  0.575905  \n",
       "...             ...       ...  \n",
       "RANI3.SA   0.110034  0.079512  \n",
       "RAPT4.SA   0.374031  0.600619  \n",
       "RCSL4.SA   0.189366  0.226100  \n",
       "RENT3.SA   0.359664  0.458572  \n",
       "SANB11.SA  0.233126  0.470607  \n",
       "SAPR11.SA  0.277473  0.500792  \n",
       "SAPR4.SA   0.301516  0.510340  \n",
       "SBSP3.SA   0.325338  0.453796  \n",
       "SEER3.SA   0.267326  0.659407  \n",
       "SLCE3.SA   0.231968  0.095573  \n",
       "SMLS3.SA   0.176703  0.550257  \n",
       "SMTO3.SA   0.316978  0.289425  \n",
       "SOMA3.SA   0.105282  0.359911  \n",
       "STBP3.SA   0.256279  0.467947  \n",
       "SUZB3.SA   0.059237 -0.178798  \n",
       "TAEE11.SA  0.229367  0.271656  \n",
       "TASA4.SA   0.054589  0.086691  \n",
       "TCSA3.SA   0.277392  0.519719  \n",
       "TEND3.SA   0.346142  0.586186  \n",
       "TIET11.SA  0.208563  0.213961  \n",
       "TOTS3.SA   0.452858  0.323290  \n",
       "TRIS3.SA   0.265609  0.585905  \n",
       "TRPL4.SA   0.237594  0.239877  \n",
       "UGPA3.SA   0.250840  0.471220  \n",
       "USIM5.SA   0.255131  0.289774  \n",
       "VALE3.SA   0.157493  0.138029  \n",
       "VIVA3.SA   0.328878  0.537041  \n",
       "VVAR3.SA   0.358932  0.344747  \n",
       "WEGE3.SA   1.000000  0.282602  \n",
       "YDUQ3.SA   0.282602  1.000000  \n",
       "\n",
       "[150 rows x 150 columns]"
      ]
     },
     "execution_count": 376,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "market_corr=market_close.pct_change().iloc[0:].corr() \n",
    "\n",
    "corr_list  = market_corr.values.tolist()\n",
    "menores_corr = []\n",
    "names = []\n",
    "for col in market_close.columns:\n",
    "    names.append(col)\n",
    "\n",
    "# Ranking das menores correlacoes\n",
    "\n",
    "corr_all = pd.DataFrame(data = corr_list, index = names, columns = names)\n",
    "corr_all"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 377,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['SUZB3.SA',\n",
       " 'BPAN4.SA',\n",
       " 'KLBN11.SA',\n",
       " 'KLBN4.SA',\n",
       " 'MRFG3.SA',\n",
       " 'PCAR3.SA',\n",
       " 'BEEF3.SA',\n",
       " 'TASA4.SA',\n",
       " 'RANI3.SA',\n",
       " 'SLCE3.SA',\n",
       " 'JBSS3.SA',\n",
       " 'NGRD3.SA',\n",
       " 'VALE3.SA',\n",
       " 'BRAP4.SA',\n",
       " 'AERI3.SA',\n",
       " 'PETZ3.SA',\n",
       " 'DMMO3.SA',\n",
       " 'CASH3.SA',\n",
       " 'OIBR4.SA',\n",
       " 'LWSA3.SA',\n",
       " 'ETER3.SA',\n",
       " 'BRFS3.SA',\n",
       " 'ODPV3.SA',\n",
       " 'RCSL4.SA',\n",
       " 'PRIO3.SA',\n",
       " 'LAME3.SA',\n",
       " 'LINX3.SA',\n",
       " 'ENAT3.SA',\n",
       " 'SOMA3.SA',\n",
       " 'LJQQ3.SA',\n",
       " 'BIDI4.SA',\n",
       " 'CSNA3.SA',\n",
       " 'CRFB3.SA',\n",
       " 'OIBR3.SA',\n",
       " 'SMTO3.SA',\n",
       " 'BTOW3.SA',\n",
       " 'LAVV3.SA',\n",
       " 'BRKM5.SA',\n",
       " 'HBSA3.SA',\n",
       " 'IRBR3.SA',\n",
       " 'CAML3.SA',\n",
       " 'TIET11.SA',\n",
       " 'ENJU3.SA',\n",
       " 'WEGE3.SA',\n",
       " 'MGLU3.SA',\n",
       " 'TRPL4.SA',\n",
       " 'TAEE11.SA',\n",
       " 'ENEV3.SA',\n",
       " 'LAME4.SA',\n",
       " 'USIM5.SA',\n",
       " 'MYPK3.SA',\n",
       " 'GGBR4.SA',\n",
       " 'POSI3.SA',\n",
       " 'GOAU4.SA',\n",
       " 'RADL3.SA',\n",
       " 'TOTS3.SA',\n",
       " 'EMBR3.SA',\n",
       " 'GNDI3.SA',\n",
       " 'CIEL3.SA',\n",
       " 'GMAT3.SA',\n",
       " 'RAIL3.SA',\n",
       " 'ALPA4.SA',\n",
       " 'PTBL3.SA',\n",
       " 'BKBR3.SA',\n",
       " 'PETR4.SA',\n",
       " 'PETR3.SA',\n",
       " 'GFSA3.SA',\n",
       " 'HAPV3.SA',\n",
       " 'BMGB4.SA',\n",
       " 'HYPE3.SA',\n",
       " 'ANIM3.SA',\n",
       " 'CSAN3.SA',\n",
       " 'ELET3.SA',\n",
       " 'FLRY3.SA',\n",
       " 'PSSA3.SA',\n",
       " 'MILS3.SA',\n",
       " 'ABEV3.SA',\n",
       " 'ELET6.SA',\n",
       " 'DTEX3.SA',\n",
       " 'NTCO3.SA',\n",
       " 'SMLS3.SA',\n",
       " 'STBP3.SA',\n",
       " 'QUAL3.SA',\n",
       " 'VVAR3.SA',\n",
       " 'SEER3.SA',\n",
       " 'CPFE3.SA',\n",
       " 'MEAL3.SA',\n",
       " 'CPLE3.SA',\n",
       " 'AZUL4.SA',\n",
       " 'CNTO3.SA',\n",
       " 'NEOE3.SA',\n",
       " 'GOLL4.SA',\n",
       " 'CPLE6.SA',\n",
       " 'GRND3.SA',\n",
       " 'MDIA3.SA',\n",
       " 'COGN3.SA',\n",
       " 'ENGI11.SA',\n",
       " 'SANB11.SA',\n",
       " 'CEAB3.SA',\n",
       " 'YDUQ3.SA']"
      ]
     },
     "execution_count": 377,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lista com menores correlacoes\n",
    "best_corr = []\n",
    "for i in range(0, len(corr_all)):\n",
    "    correlation_list = corr_all.mean().sort_values(ascending = True) #True = menores correlacoes\n",
    "    best_corr.append(correlation_list.index[i])\n",
    "    \n",
    "best_corr = Remove(best_corr[:100])\n",
    "best_corr = best_corr[:]\n",
    "best_corr\n",
    "# best_corr.remove(\"SPRI5.SA\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "<div id=\"Tópico 2\">\n",
    "    <div class=\"alert alert-block alert-info\" style=\"margin-top: 0px\"> \n",
    "</div> </div> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 378,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  100 of 100 downloaded\n"
     ]
    }
   ],
   "source": [
    "# Analise dos ativos filtrados\n",
    "stocks_all=yahoo(best_corr,S_Day, S_Month, S_Year, E_Day, E_Month, E_Year)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 379,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Insira a taxa de comparação para o Sharpe:\n",
      "\n",
      "===========> ABEV3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  126\n",
      "              Negative -  117\n",
      "              Pct Up   - 51.85\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -1.208\n",
      "\n",
      "              R. price    : 12.09362\n",
      "              Coef_price  : 0.01347586\n",
      "\n",
      "              R. intercept: 0.00111\n",
      "              Coef        : -0.00000033\n",
      "\n",
      "              Target_sell : 15.27\n",
      "              Actual_price: 15.15\n",
      "              Target_buy  : 15.07\n",
      "\n",
      "              Base_price  : 13.62\n",
      "              Stop_loss   : -10.09%\n",
      "\n",
      "              Stock_return: 21.30%\n",
      "\n",
      "\n",
      "===========> AERI3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  42\n",
      "              Negative -  44\n",
      "              Pct Up   - 48.84\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  2\n",
      "              Negative -  2\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.362\n",
      "\n",
      "              R. price    : -3.25147\n",
      "              Coef_price  : 0.05450382\n",
      "\n",
      "              R. intercept: 0.00028\n",
      "              Coef        : 0.00001334\n",
      "\n",
      "              Target_sell : 9.50\n",
      "              Actual_price: 9.10\n",
      "              Target_buy  : 9.00\n",
      "\n",
      "              Base_price  : 2.92\n",
      "              Stop_loss   : -67.87%\n",
      "\n",
      "              Stock_return: 49.18%\n",
      "\n",
      "\n",
      "===========> ALPA4.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  128\n",
      "              Negative -  115\n",
      "              Pct Up   - 52.67\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.392\n",
      "\n",
      "              R. price    : 26.53894\n",
      "              Coef_price  : 0.06454937\n",
      "\n",
      "              R. intercept: 0.00537\n",
      "              Coef        : -0.00002729\n",
      "\n",
      "              Target_sell : 37.06\n",
      "              Actual_price: 36.69\n",
      "              Target_buy  : 34.74\n",
      "\n",
      "              Base_price  : 31.61\n",
      "              Stop_loss   : -13.83%\n",
      "\n",
      "              Stock_return: 50.62%\n",
      "\n",
      "\n",
      "===========> ANIM3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  122\n",
      "              Negative -  121\n",
      "              Pct Up   - 50.21\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.924\n",
      "\n",
      "              R. price    : 25.49908\n",
      "              Coef_price  : 0.00028057\n",
      "\n",
      "              R. intercept: 0.00868\n",
      "              Coef        : -0.00007940\n",
      "\n",
      "              Target_sell : 8.94\n",
      "              Actual_price: 9.13\n",
      "              Target_buy  : 8.94\n",
      "\n",
      "              Base_price  : 17.31\n",
      "              Stop_loss   : 89.63%\n",
      "\n",
      "              Stock_return: -56.27%\n",
      "\n",
      "\n",
      "===========> AZUL4.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  124\n",
      "              Negative -  119\n",
      "              Pct Up   - 51.03\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.508\n",
      "\n",
      "              R. price    : 12.52141\n",
      "              Coef_price  : 0.12242003\n",
      "\n",
      "              R. intercept: 0.00453\n",
      "              Coef        : -0.00000420\n",
      "\n",
      "              Target_sell : 40.77\n",
      "              Actual_price: 37.47\n",
      "              Target_buy  : 36.18\n",
      "\n",
      "              Base_price  : 25.00\n",
      "              Stop_loss   : -33.29%\n",
      "\n",
      "              Stock_return: 96.28%\n",
      "\n",
      "\n",
      "===========> BEEF3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  115\n",
      "              Negative -  128\n",
      "              Pct Up   - 47.33\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  6\n",
      "              Negative -  6\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -1.131\n",
      "\n",
      "              R. price    : 12.66665\n",
      "              Coef_price  : -0.01276950\n",
      "\n",
      "              R. intercept: 0.00754\n",
      "              Coef        : -0.00005055\n",
      "\n",
      "              Target_sell : 9.81\n",
      "              Actual_price: 9.83\n",
      "              Target_buy  : 9.93\n",
      "\n",
      "              Base_price  : 11.25\n",
      "              Stop_loss   : 14.43%\n",
      "\n",
      "              Stock_return: 29.00%\n",
      "\n",
      "\n",
      "===========> BIDI4.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  138\n",
      "              Negative -  104\n",
      "              Pct Up   - 57.02\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  10\n",
      "              Negative -  2\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 1.000\n",
      "\n",
      "              R. price    : 3.33513\n",
      "              Coef_price  : 0.17122022\n",
      "\n",
      "              R. intercept: 0.00454\n",
      "              Coef        : 0.00002178\n",
      "\n",
      "              Target_sell : 56.33\n",
      "              Actual_price: 50.98\n",
      "              Target_buy  : 47.37\n",
      "\n",
      "              Base_price  : 27.16\n",
      "              Stop_loss   : -46.73%\n",
      "\n",
      "              Stock_return: 373.79%\n",
      "\n",
      "\n",
      "===========> BKBR3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  123\n",
      "              Negative -  119\n",
      "              Pct Up   - 50.83\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -2.513\n",
      "\n",
      "              R. price    : 10.76759\n",
      "              Coef_price  : -0.00250519\n",
      "\n",
      "              R. intercept: 0.00375\n",
      "              Coef        : -0.00002547\n",
      "\n",
      "              Target_sell : 9.32\n",
      "              Actual_price: 9.48\n",
      "              Target_buy  : 9.34\n",
      "\n",
      "              Base_price  : 10.12\n",
      "              Stop_loss   : 6.79%\n",
      "\n",
      "              Stock_return: -0.73%\n",
      "\n",
      "\n",
      "===========> BMGB4.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  120\n",
      "              Negative -  122\n",
      "              Pct Up   - 49.59\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -4.517\n",
      "\n",
      "              R. price    : 4.65172\n",
      "              Coef_price  : 0.00232217\n",
      "\n",
      "              R. intercept: 0.00522\n",
      "              Coef        : -0.00002797\n",
      "\n",
      "              Target_sell : 5.15\n",
      "              Actual_price: 5.15\n",
      "              Target_buy  : 5.14\n",
      "\n",
      "              Base_price  : 4.90\n",
      "              Stop_loss   : -4.84%\n",
      "\n",
      "              Stock_return: 41.10%\n",
      "\n",
      "\n",
      "===========> BPAN4.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  120\n",
      "              Negative -  123\n",
      "              Pct Up   - 49.38\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  6\n",
      "              Negative -  6\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.002\n",
      "\n",
      "              R. price    : -24.71942\n",
      "              Coef_price  : 0.47007249\n",
      "\n",
      "              R. intercept: -2.45786\n",
      "              Coef        : 0.03609899\n",
      "\n",
      "              Target_sell : 13.75\n",
      "              Actual_price: 10.78\n",
      "              Target_buy  : 8.24\n",
      "\n",
      "              Base_price  : -7.42\n",
      "              Stop_loss   : -168.79%\n",
      "\n",
      "              Stock_return: 115.60%\n",
      "\n",
      "\n",
      "===========> BRAP4.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  128\n",
      "              Negative -  115\n",
      "              Pct Up   - 52.67\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  11\n",
      "              Negative -  1\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.930\n",
      "\n",
      "              R. price    : 25.17429\n",
      "              Coef_price  : 0.17967811\n",
      "\n",
      "              R. intercept: 0.00555\n",
      "              Coef        : -0.00001401\n",
      "\n",
      "              Target_sell : 68.41\n",
      "              Actual_price: 65.37\n",
      "              Target_buy  : 57.20\n",
      "\n",
      "              Base_price  : 45.27\n",
      "              Stop_loss   : -30.75%\n",
      "\n",
      "              Stock_return: 138.58%\n",
      "\n",
      "\n",
      "===========> BRFS3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  112\n",
      "              Negative -  131\n",
      "              Pct Up   - 46.09\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.653\n",
      "\n",
      "              R. price    : 19.52637\n",
      "              Coef_price  : 0.01031214\n",
      "\n",
      "              R. intercept: 0.00526\n",
      "              Coef        : -0.00002224\n",
      "\n",
      "              Target_sell : 24.72\n",
      "              Actual_price: 24.39\n",
      "              Target_buy  : 24.47\n",
      "\n",
      "              Base_price  : 21.96\n",
      "              Stop_loss   : -9.97%\n",
      "\n",
      "              Stock_return: 68.09%\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "===========> BRKM5.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  122\n",
      "              Negative -  121\n",
      "              Pct Up   - 50.21\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  9\n",
      "              Negative -  3\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 1.357\n",
      "\n",
      "              R. price    : 20.50911\n",
      "              Coef_price  : 0.03155663\n",
      "\n",
      "              R. intercept: 0.00275\n",
      "              Coef        : 0.00000826\n",
      "\n",
      "              Target_sell : 37.70\n",
      "              Actual_price: 37.83\n",
      "              Target_buy  : 36.53\n",
      "\n",
      "              Base_price  : 29.17\n",
      "              Stop_loss   : -22.89%\n",
      "\n",
      "              Stock_return: 113.73%\n",
      "\n",
      "\n",
      "===========> BTOW3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  106\n",
      "              Negative -  137\n",
      "              Pct Up   - 43.62\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  5\n",
      "              Negative -  7\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.038\n",
      "\n",
      "              R. price    : 97.21789\n",
      "              Coef_price  : -0.07517274\n",
      "\n",
      "              R. intercept: 0.01304\n",
      "              Coef        : -0.00009534\n",
      "\n",
      "              Target_sell : 59.50\n",
      "              Actual_price: 59.36\n",
      "              Target_buy  : 64.11\n",
      "\n",
      "              Base_price  : 78.28\n",
      "              Stop_loss   : 31.88%\n",
      "\n",
      "              Stock_return: 16.41%\n",
      "\n",
      "\n",
      "===========> CAML3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  126\n",
      "              Negative -  117\n",
      "              Pct Up   - 51.85\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -1.116\n",
      "\n",
      "              R. price    : 10.03244\n",
      "              Coef_price  : 0.00816934\n",
      "\n",
      "              R. intercept: 0.00642\n",
      "              Coef        : -0.00004126\n",
      "\n",
      "              Target_sell : 10.58\n",
      "              Actual_price: 10.29\n",
      "              Target_buy  : 10.50\n",
      "\n",
      "              Base_price  : 10.16\n",
      "              Stop_loss   : -1.25%\n",
      "\n",
      "              Stock_return: 32.26%\n",
      "\n",
      "\n",
      "===========> CASH3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  51\n",
      "              Negative -  38\n",
      "              Pct Up   - 57.30\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  3\n",
      "              Negative -  1\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 1.572\n",
      "\n",
      "              R. price    : -7.91209\n",
      "              Coef_price  : 0.12666217\n",
      "\n",
      "              R. intercept: -0.00154\n",
      "              Coef        : 0.00004822\n",
      "\n",
      "              Target_sell : 25.22\n",
      "              Actual_price: 23.02\n",
      "              Target_buy  : 22.27\n",
      "\n",
      "              Base_price  : 7.55\n",
      "              Stop_loss   : -67.19%\n",
      "\n",
      "              Stock_return: 142.57%\n",
      "\n",
      "\n",
      "===========> CEAB3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  118\n",
      "              Negative -  124\n",
      "              Pct Up   - 48.76\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.628\n",
      "\n",
      "              R. price    : 9.43923\n",
      "              Coef_price  : 0.01422482\n",
      "\n",
      "              R. intercept: 0.00922\n",
      "              Coef        : -0.00005379\n",
      "\n",
      "              Target_sell : 11.22\n",
      "              Actual_price: 11.00\n",
      "              Target_buy  : 11.06\n",
      "\n",
      "              Base_price  : 10.22\n",
      "              Stop_loss   : -7.10%\n",
      "\n",
      "              Stock_return: 54.93%\n",
      "\n",
      "\n",
      "===========> CIEL3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  111\n",
      "              Negative -  132\n",
      "              Pct Up   - 45.68\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  5\n",
      "              Negative -  7\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -5.583\n",
      "\n",
      "              R. price    : 4.64331\n",
      "              Coef_price  : -0.00444485\n",
      "\n",
      "              R. intercept: -0.00006\n",
      "              Coef        : -0.00000207\n",
      "\n",
      "              Target_sell : 3.61\n",
      "              Actual_price: 3.63\n",
      "              Target_buy  : 3.63\n",
      "\n",
      "              Base_price  : 4.14\n",
      "              Stop_loss   : 13.96%\n",
      "\n",
      "              Stock_return: -22.51%\n",
      "\n",
      "\n",
      "===========> CNTO3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  103\n",
      "              Negative -  140\n",
      "              Pct Up   - 42.39\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  6\n",
      "              Negative -  6\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.768\n",
      "\n",
      "              R. price    : 30.22152\n",
      "              Coef_price  : -0.02237776\n",
      "\n",
      "              R. intercept: 0.00234\n",
      "              Coef        : -0.00001247\n",
      "\n",
      "              Target_sell : 25.64\n",
      "              Actual_price: 26.69\n",
      "              Target_buy  : 26.24\n",
      "\n",
      "              Base_price  : 28.46\n",
      "              Stop_loss   : 6.62%\n",
      "\n",
      "              Stock_return: 2.03%\n",
      "\n",
      "\n",
      "===========> COGN3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  109\n",
      "              Negative -  134\n",
      "              Pct Up   - 44.86\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  5\n",
      "              Negative -  7\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -2.414\n",
      "\n",
      "              R. price    : 6.48579\n",
      "              Coef_price  : -0.00881663\n",
      "\n",
      "              R. intercept: 0.00498\n",
      "              Coef        : -0.00004296\n",
      "\n",
      "              Target_sell : 3.96\n",
      "              Actual_price: 3.84\n",
      "              Target_buy  : 3.99\n",
      "\n",
      "              Base_price  : 5.16\n",
      "              Stop_loss   : 34.45%\n",
      "\n",
      "              Stock_return: -24.11%\n",
      "\n",
      "\n",
      "===========> CPFE3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  129\n",
      "              Negative -  114\n",
      "              Pct Up   - 53.09\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  6\n",
      "              Negative -  6\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.085\n",
      "\n",
      "              R. price    : 27.60486\n",
      "              Coef_price  : 0.01499833\n",
      "\n",
      "              R. intercept: 0.00347\n",
      "              Coef        : -0.00001884\n",
      "\n",
      "              Target_sell : 30.85\n",
      "              Actual_price: 30.27\n",
      "              Target_buy  : 30.39\n",
      "\n",
      "              Base_price  : 28.94\n",
      "              Stop_loss   : -4.40%\n",
      "\n",
      "              Stock_return: 26.12%\n",
      "\n",
      "\n",
      "===========> CPLE3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  122\n",
      "              Negative -  121\n",
      "              Pct Up   - 50.21\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  5\n",
      "              Negative -  7\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -1.600\n",
      "\n",
      "              R. price    : 64.54240\n",
      "              Coef_price  : -0.06518663\n",
      "\n",
      "              R. intercept: 0.00621\n",
      "              Coef        : -0.00007370\n",
      "\n",
      "              Target_sell : 6.50\n",
      "              Actual_price: 6.71\n",
      "              Target_buy  : 6.94\n",
      "\n",
      "              Base_price  : 35.62\n",
      "              Stop_loss   : 430.91%\n",
      "\n",
      "              Stock_return: -88.37%\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "===========> CPLE6.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  122\n",
      "              Negative -  121\n",
      "              Pct Up   - 50.21\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -1.359\n",
      "\n",
      "              R. price    : 66.14247\n",
      "              Coef_price  : -0.05748058\n",
      "\n",
      "              R. intercept: 0.00857\n",
      "              Coef        : -0.00008794\n",
      "\n",
      "              Target_sell : 6.75\n",
      "              Actual_price: 6.98\n",
      "              Target_buy  : 7.16\n",
      "\n",
      "              Base_price  : 36.56\n",
      "              Stop_loss   : 423.76%\n",
      "\n",
      "              Stock_return: -86.60%\n",
      "\n",
      "\n",
      "===========> CRFB3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  122\n",
      "              Negative -  121\n",
      "              Pct Up   - 50.21\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  6\n",
      "              Negative -  6\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -2.433\n",
      "\n",
      "              R. price    : 19.72816\n",
      "              Coef_price  : -0.00061119\n",
      "\n",
      "              R. intercept: -0.00200\n",
      "              Coef        : 0.00001960\n",
      "\n",
      "              Target_sell : 20.45\n",
      "              Actual_price: 22.22\n",
      "              Target_buy  : 20.46\n",
      "\n",
      "              Base_price  : 20.97\n",
      "              Stop_loss   : -5.61%\n",
      "\n",
      "              Stock_return: 4.32%\n",
      "\n",
      "\n",
      "===========> CSAN3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  118\n",
      "              Negative -  125\n",
      "              Pct Up   - 48.56\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 1.163\n",
      "\n",
      "              R. price    : 61.76347\n",
      "              Coef_price  : 0.10061192\n",
      "\n",
      "              R. intercept: 0.00362\n",
      "              Coef        : -0.00000944\n",
      "\n",
      "              Target_sell : 96.48\n",
      "              Actual_price: 90.80\n",
      "              Target_buy  : 87.26\n",
      "\n",
      "              Base_price  : 76.28\n",
      "              Stop_loss   : -15.99%\n",
      "\n",
      "              Stock_return: 66.85%\n",
      "\n",
      "\n",
      "===========> CSNA3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  130\n",
      "              Negative -  113\n",
      "              Pct Up   - 53.50\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  10\n",
      "              Negative -  2\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.875\n",
      "\n",
      "              R. price    : 3.14434\n",
      "              Coef_price  : 0.13428327\n",
      "\n",
      "              R. intercept: 0.00959\n",
      "              Coef        : -0.00001877\n",
      "\n",
      "              Target_sell : 37.00\n",
      "              Actual_price: 35.14\n",
      "              Target_buy  : 32.43\n",
      "\n",
      "              Base_price  : 19.14\n",
      "              Stop_loss   : -45.53%\n",
      "\n",
      "              Stock_return: 398.44%\n",
      "\n",
      "\n",
      "===========> DMMO3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  112\n",
      "              Negative -  131\n",
      "              Pct Up   - 46.09\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -10.950\n",
      "\n",
      "              R. price    : 1.37671\n",
      "              Coef_price  : -0.00127478\n",
      "\n",
      "              R. intercept: 0.01821\n",
      "              Coef        : -0.00012047\n",
      "\n",
      "              Target_sell : 0.88\n",
      "              Actual_price: 0.87\n",
      "              Target_buy  : 0.88\n",
      "\n",
      "              Base_price  : 1.12\n",
      "              Stop_loss   : 29.11%\n",
      "\n",
      "              Stock_return: 35.94%\n",
      "\n",
      "\n",
      "===========> DTEX3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  122\n",
      "              Negative -  121\n",
      "              Pct Up   - 50.21\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  9\n",
      "              Negative -  3\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.269\n",
      "\n",
      "              R. price    : 10.01654\n",
      "              Coef_price  : 0.04655158\n",
      "\n",
      "              R. intercept: 0.00691\n",
      "              Coef        : -0.00002972\n",
      "\n",
      "              Target_sell : 19.64\n",
      "              Actual_price: 18.76\n",
      "              Target_buy  : 18.75\n",
      "\n",
      "              Base_price  : 14.39\n",
      "              Stop_loss   : -23.30%\n",
      "\n",
      "              Stock_return: 95.01%\n",
      "\n",
      "\n",
      "===========> ELET3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  117\n",
      "              Negative -  126\n",
      "              Pct Up   - 48.15\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  6\n",
      "              Negative -  6\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.628\n",
      "\n",
      "              R. price    : 25.32078\n",
      "              Coef_price  : 0.03707293\n",
      "\n",
      "              R. intercept: 0.00623\n",
      "              Coef        : -0.00002878\n",
      "\n",
      "              Target_sell : 33.76\n",
      "              Actual_price: 33.77\n",
      "              Target_buy  : 32.54\n",
      "\n",
      "              Base_price  : 29.55\n",
      "              Stop_loss   : -12.51%\n",
      "\n",
      "              Stock_return: 69.27%\n",
      "\n",
      "\n",
      "===========> ELET6.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  120\n",
      "              Negative -  123\n",
      "              Pct Up   - 49.38\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  6\n",
      "              Negative -  6\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.514\n",
      "\n",
      "              R. price    : 27.26596\n",
      "              Coef_price  : 0.02861091\n",
      "\n",
      "              R. intercept: 0.00470\n",
      "              Coef        : -0.00002103\n",
      "\n",
      "              Target_sell : 34.31\n",
      "              Actual_price: 34.26\n",
      "              Target_buy  : 33.34\n",
      "\n",
      "              Base_price  : 30.76\n",
      "              Stop_loss   : -10.21%\n",
      "\n",
      "              Stock_return: 51.93%\n",
      "\n",
      "\n",
      "===========> EMBR3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  122\n",
      "              Negative -  121\n",
      "              Pct Up   - 50.21\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.610\n",
      "\n",
      "              R. price    : 6.94689\n",
      "              Coef_price  : 0.01284582\n",
      "\n",
      "              R. intercept: -0.00427\n",
      "              Coef        : 0.00005342\n",
      "\n",
      "              Target_sell : 13.60\n",
      "              Actual_price: 13.17\n",
      "              Target_buy  : 13.43\n",
      "\n",
      "              Base_price  : 10.06\n",
      "              Stop_loss   : -23.62%\n",
      "\n",
      "              Stock_return: 41.31%\n",
      "\n",
      "\n",
      "===========> ENAT3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  123\n",
      "              Negative -  120\n",
      "              Pct Up   - 50.62\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.231\n",
      "\n",
      "              R. price    : 8.95564\n",
      "              Coef_price  : 0.01727597\n",
      "\n",
      "              R. intercept: 0.00359\n",
      "              Coef        : -0.00000232\n",
      "\n",
      "              Target_sell : 15.69\n",
      "              Actual_price: 15.48\n",
      "              Target_buy  : 15.42\n",
      "\n",
      "              Base_price  : 12.22\n",
      "              Stop_loss   : -21.07%\n",
      "\n",
      "              Stock_return: 98.46%\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "===========> ENEV3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  133\n",
      "              Negative -  110\n",
      "              Pct Up   - 54.73\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  9\n",
      "              Negative -  3\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.171\n",
      "\n",
      "              R. price    : 8.49535\n",
      "              Coef_price  : 0.03569051\n",
      "\n",
      "              R. intercept: 0.00428\n",
      "              Coef        : -0.00001121\n",
      "\n",
      "              Target_sell : 16.66\n",
      "              Actual_price: 16.42\n",
      "              Target_buy  : 16.08\n",
      "\n",
      "              Base_price  : 12.46\n",
      "              Stop_loss   : -24.13%\n",
      "\n",
      "              Stock_return: 90.93%\n",
      "\n",
      "\n",
      "===========> ENGI11.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  123\n",
      "              Negative -  120\n",
      "              Pct Up   - 50.62\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  6\n",
      "              Negative -  6\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.034\n",
      "\n",
      "              R. price    : 44.14732\n",
      "              Coef_price  : 0.01013235\n",
      "\n",
      "              R. intercept: 0.00355\n",
      "              Coef        : -0.00002160\n",
      "\n",
      "              Target_sell : 44.32\n",
      "              Actual_price: 44.33\n",
      "              Target_buy  : 43.88\n",
      "\n",
      "              Base_price  : 44.24\n",
      "              Stop_loss   : -0.21%\n",
      "\n",
      "              Stock_return: 16.90%\n",
      "\n",
      "\n",
      "===========> ENJU3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  45\n",
      "              Negative -  44\n",
      "              Pct Up   - 50.56\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  3\n",
      "              Negative -  1\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.677\n",
      "\n",
      "              R. price    : -4.38633\n",
      "              Coef_price  : 0.07451156\n",
      "\n",
      "              R. intercept: 0.00140\n",
      "              Coef        : -0.00000663\n",
      "\n",
      "              Target_sell : 11.09\n",
      "              Actual_price: 10.25\n",
      "              Target_buy  : 10.31\n",
      "\n",
      "              Base_price  : 2.93\n",
      "              Stop_loss   : -71.40%\n",
      "\n",
      "              Stock_return: 5.02%\n",
      "\n",
      "\n",
      "===========> ETER3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  140\n",
      "              Negative -  103\n",
      "              Pct Up   - 57.61\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.749\n",
      "\n",
      "              R. price    : 0.38643\n",
      "              Coef_price  : 0.06354985\n",
      "\n",
      "              R. intercept: 0.00677\n",
      "              Coef        : 0.00001863\n",
      "\n",
      "              Target_sell : 18.71\n",
      "              Actual_price: 18.50\n",
      "              Target_buy  : 17.56\n",
      "\n",
      "              Base_price  : 9.44\n",
      "              Stop_loss   : -48.96%\n",
      "\n",
      "              Stock_return: 556.03%\n",
      "\n",
      "\n",
      "===========> FLRY3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  115\n",
      "              Negative -  128\n",
      "              Pct Up   - 47.33\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  6\n",
      "              Negative -  6\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.299\n",
      "\n",
      "              R. price    : 22.62093\n",
      "              Coef_price  : 0.01929411\n",
      "\n",
      "              R. intercept: 0.00388\n",
      "              Coef        : -0.00002230\n",
      "\n",
      "              Target_sell : 25.41\n",
      "              Actual_price: 25.16\n",
      "              Target_buy  : 24.93\n",
      "\n",
      "              Base_price  : 23.89\n",
      "              Stop_loss   : -5.05%\n",
      "\n",
      "              Stock_return: 25.36%\n",
      "\n",
      "\n",
      "===========> GFSA3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  112\n",
      "              Negative -  131\n",
      "              Pct Up   - 46.09\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -3.367\n",
      "\n",
      "              R. price    : 4.62351\n",
      "              Coef_price  : 0.00050981\n",
      "\n",
      "              R. intercept: 0.00291\n",
      "              Coef        : -0.00001247\n",
      "\n",
      "              Target_sell : 4.88\n",
      "              Actual_price: 4.66\n",
      "              Target_buy  : 4.88\n",
      "\n",
      "              Base_price  : 4.64\n",
      "              Stop_loss   : -0.39%\n",
      "\n",
      "              Stock_return: 9.65%\n",
      "\n",
      "\n",
      "===========> GGBR4.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  131\n",
      "              Negative -  112\n",
      "              Pct Up   - 53.91\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  10\n",
      "              Negative -  2\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.957\n",
      "\n",
      "              R. price    : 10.85270\n",
      "              Coef_price  : 0.07070351\n",
      "\n",
      "              R. intercept: 0.00825\n",
      "              Coef        : -0.00002722\n",
      "\n",
      "              Target_sell : 28.68\n",
      "              Actual_price: 28.60\n",
      "              Target_buy  : 26.75\n",
      "\n",
      "              Base_price  : 19.73\n",
      "              Stop_loss   : -31.03%\n",
      "\n",
      "              Stock_return: 197.30%\n",
      "\n",
      "\n",
      "===========> GMAT3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  55\n",
      "              Negative -  53\n",
      "              Pct Up   - 50.93\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  4\n",
      "              Negative -  1\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -9.153\n",
      "\n",
      "              R. price    : -2.29437\n",
      "              Coef_price  : 0.04875048\n",
      "\n",
      "              R. intercept: 0.00010\n",
      "              Coef        : -0.00000462\n",
      "\n",
      "              Target_sell : 7.72\n",
      "              Actual_price: 7.75\n",
      "              Target_buy  : 7.35\n",
      "\n",
      "              Base_price  : 2.73\n",
      "              Stop_loss   : -64.80%\n",
      "\n",
      "              Stock_return: -13.31%\n",
      "\n",
      "\n",
      "===========> GNDI3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  124\n",
      "              Negative -  119\n",
      "              Pct Up   - 51.03\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.953\n",
      "\n",
      "              R. price    : 52.12300\n",
      "              Coef_price  : 0.15282489\n",
      "\n",
      "              R. intercept: 0.00534\n",
      "              Coef        : -0.00002032\n",
      "\n",
      "              Target_sell : 91.32\n",
      "              Actual_price: 84.57\n",
      "              Target_buy  : 78.37\n",
      "\n",
      "              Base_price  : 68.35\n",
      "              Stop_loss   : -19.18%\n",
      "\n",
      "              Stock_return: 76.19%\n",
      "\n",
      "\n",
      "===========> GOAU4.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  134\n",
      "              Negative -  109\n",
      "              Pct Up   - 55.14\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  10\n",
      "              Negative -  2\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.288\n",
      "\n",
      "              R. price    : 4.93863\n",
      "              Coef_price  : 0.03166866\n",
      "\n",
      "              R. intercept: 0.00816\n",
      "              Coef        : -0.00002764\n",
      "\n",
      "              Target_sell : 12.58\n",
      "              Actual_price: 12.74\n",
      "              Target_buy  : 12.19\n",
      "\n",
      "              Base_price  : 8.84\n",
      "              Stop_loss   : -30.62%\n",
      "\n",
      "              Stock_return: 189.55%\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "===========> GOLL4.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  112\n",
      "              Negative -  131\n",
      "              Pct Up   - 46.09\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.149\n",
      "\n",
      "              R. price    : 13.34690\n",
      "              Coef_price  : 0.04773135\n",
      "\n",
      "              R. intercept: 0.00828\n",
      "              Coef        : -0.00004064\n",
      "\n",
      "              Target_sell : 21.63\n",
      "              Actual_price: 20.58\n",
      "              Target_buy  : 20.64\n",
      "\n",
      "              Base_price  : 16.96\n",
      "              Stop_loss   : -17.57%\n",
      "\n",
      "              Stock_return: 67.32%\n",
      "\n",
      "\n",
      "===========> GRND3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  119\n",
      "              Negative -  124\n",
      "              Pct Up   - 48.97\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -4.927\n",
      "\n",
      "              R. price    : 7.32315\n",
      "              Coef_price  : 0.00328465\n",
      "\n",
      "              R. intercept: 0.00098\n",
      "              Coef        : -0.00000415\n",
      "\n",
      "              Target_sell : 7.96\n",
      "              Actual_price: 7.80\n",
      "              Target_buy  : 7.93\n",
      "\n",
      "              Base_price  : 7.56\n",
      "              Stop_loss   : -3.06%\n",
      "\n",
      "              Stock_return: 4.70%\n",
      "\n",
      "\n",
      "===========> HAPV3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  136\n",
      "              Negative -  107\n",
      "              Pct Up   - 55.97\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  9\n",
      "              Negative -  3\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.071\n",
      "\n",
      "              R. price    : 9.70069\n",
      "              Coef_price  : 0.02909972\n",
      "\n",
      "              R. intercept: 0.00576\n",
      "              Coef        : -0.00002595\n",
      "\n",
      "              Target_sell : 15.44\n",
      "              Actual_price: 15.15\n",
      "              Target_buy  : 15.00\n",
      "\n",
      "              Base_price  : 12.43\n",
      "              Stop_loss   : -17.99%\n",
      "\n",
      "              Stock_return: 70.80%\n",
      "\n",
      "\n",
      "===========> HBSA3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  61\n",
      "              Negative -  58\n",
      "              Pct Up   - 51.26\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  3\n",
      "              Negative -  3\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -8.305\n",
      "\n",
      "              R. price    : -1.51828\n",
      "              Coef_price  : 0.03878114\n",
      "\n",
      "              R. intercept: 0.00021\n",
      "              Coef        : -0.00000789\n",
      "\n",
      "              Target_sell : 5.90\n",
      "              Actual_price: 5.94\n",
      "              Target_buy  : 5.68\n",
      "\n",
      "              Base_price  : 2.21\n",
      "              Stop_loss   : -62.78%\n",
      "\n",
      "              Stock_return: -19.95%\n",
      "\n",
      "\n",
      "===========> HYPE3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  130\n",
      "              Negative -  113\n",
      "              Pct Up   - 53.50\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  5\n",
      "              Negative -  7\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.812\n",
      "\n",
      "              R. price    : 30.09822\n",
      "              Coef_price  : 0.00897609\n",
      "\n",
      "              R. intercept: 0.00110\n",
      "              Coef        : -0.00000380\n",
      "\n",
      "              Target_sell : 32.19\n",
      "              Actual_price: 32.16\n",
      "              Target_buy  : 31.91\n",
      "\n",
      "              Base_price  : 31.13\n",
      "              Stop_loss   : -3.21%\n",
      "\n",
      "              Stock_return: 8.61%\n",
      "\n",
      "\n",
      "===========> IRBR3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  113\n",
      "              Negative -  130\n",
      "              Pct Up   - 46.50\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  5\n",
      "              Negative -  7\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -2.990\n",
      "\n",
      "              R. price    : 9.50739\n",
      "              Coef_price  : -0.01484144\n",
      "\n",
      "              R. intercept: -0.00032\n",
      "              Coef        : -0.00000260\n",
      "\n",
      "              Target_sell : 6.10\n",
      "              Actual_price: 6.10\n",
      "              Target_buy  : 6.19\n",
      "\n",
      "              Base_price  : 7.80\n",
      "              Stop_loss   : 27.93%\n",
      "\n",
      "              Stock_return: -40.66%\n",
      "\n",
      "\n",
      "===========> JBSS3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  117\n",
      "              Negative -  126\n",
      "              Pct Up   - 48.15\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  6\n",
      "              Negative -  6\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.180\n",
      "\n",
      "              R. price    : 20.61184\n",
      "              Coef_price  : 0.01745266\n",
      "\n",
      "              R. intercept: -0.00013\n",
      "              Coef        : 0.00001363\n",
      "\n",
      "              Target_sell : 27.86\n",
      "              Actual_price: 28.67\n",
      "              Target_buy  : 27.37\n",
      "\n",
      "              Base_price  : 24.64\n",
      "              Stop_loss   : -14.05%\n",
      "\n",
      "              Stock_return: 36.01%\n",
      "\n",
      "\n",
      "===========> KLBN11.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  123\n",
      "              Negative -  119\n",
      "              Pct Up   - 50.83\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.649\n",
      "\n",
      "              R. price    : 17.92028\n",
      "              Coef_price  : 0.04585786\n",
      "\n",
      "              R. intercept: 0.00524\n",
      "              Coef        : -0.00002087\n",
      "\n",
      "              Target_sell : 29.27\n",
      "              Actual_price: 28.51\n",
      "              Target_buy  : 27.96\n",
      "\n",
      "              Base_price  : 23.21\n",
      "              Stop_loss   : -18.57%\n",
      "\n",
      "              Stock_return: 81.25%\n",
      "\n",
      "\n",
      "===========> KLBN4.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  130\n",
      "              Negative -  113\n",
      "              Pct Up   - 53.50\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  9\n",
      "              Negative -  3\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -2.253\n",
      "\n",
      "              R. price    : 3.51225\n",
      "              Coef_price  : 0.00958910\n",
      "\n",
      "              R. intercept: 0.00525\n",
      "              Coef        : -0.00002101\n",
      "\n",
      "              Target_sell : 5.73\n",
      "              Actual_price: 5.63\n",
      "              Target_buy  : 5.68\n",
      "\n",
      "              Base_price  : 4.57\n",
      "              Stop_loss   : -18.81%\n",
      "\n",
      "              Stock_return: 79.87%\n",
      "\n",
      "\n",
      "===========> LAME3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  129\n",
      "              Negative -  114\n",
      "              Pct Up   - 53.09\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  6\n",
      "              Negative -  6\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.153\n",
      "\n",
      "              R. price    : 24.67828\n",
      "              Coef_price  : -0.01585542\n",
      "\n",
      "              R. intercept: 0.00728\n",
      "              Coef        : -0.00004439\n",
      "\n",
      "              Target_sell : 20.29\n",
      "              Actual_price: 20.48\n",
      "              Target_buy  : 20.61\n",
      "\n",
      "              Base_price  : 22.58\n",
      "              Stop_loss   : 10.25%\n",
      "\n",
      "              Stock_return: 33.59%\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "===========> LAME4.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  123\n",
      "              Negative -  120\n",
      "              Pct Up   - 50.62\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  6\n",
      "              Negative -  6\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.379\n",
      "\n",
      "              R. price    : 29.71248\n",
      "              Coef_price  : -0.02213143\n",
      "\n",
      "              R. intercept: 0.00801\n",
      "              Coef        : -0.00005705\n",
      "\n",
      "              Target_sell : 21.66\n",
      "              Actual_price: 21.61\n",
      "              Target_buy  : 22.15\n",
      "\n",
      "              Base_price  : 25.66\n",
      "              Stop_loss   : 18.74%\n",
      "\n",
      "              Stock_return: 14.46%\n",
      "\n",
      "\n",
      "===========> LAVV3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  70\n",
      "              Negative -  63\n",
      "              Pct Up   - 52.63\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  2\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -5.259\n",
      "\n",
      "              R. price    : -1.30607\n",
      "              Coef_price  : 0.04639270\n",
      "\n",
      "              R. intercept: -0.00042\n",
      "              Coef        : 0.00000031\n",
      "\n",
      "              Target_sell : 7.81\n",
      "              Actual_price: 7.70\n",
      "              Target_buy  : 7.44\n",
      "\n",
      "              Base_price  : 3.20\n",
      "              Stop_loss   : -58.48%\n",
      "\n",
      "              Stock_return: -13.09%\n",
      "\n",
      "\n",
      "===========> LINX3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  132\n",
      "              Negative -  111\n",
      "              Pct Up   - 54.32\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.676\n",
      "\n",
      "              R. price    : 20.52249\n",
      "              Coef_price  : 0.08809400\n",
      "\n",
      "              R. intercept: 0.00712\n",
      "              Coef        : -0.00003129\n",
      "\n",
      "              Target_sell : 39.30\n",
      "              Actual_price: 37.78\n",
      "              Target_buy  : 35.98\n",
      "\n",
      "              Base_price  : 29.15\n",
      "              Stop_loss   : -22.84%\n",
      "\n",
      "              Stock_return: 94.94%\n",
      "\n",
      "\n",
      "===========> LJQQ3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  78\n",
      "              Negative -  73\n",
      "              Pct Up   - 51.66\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  4\n",
      "              Negative -  3\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.615\n",
      "\n",
      "              R. price    : -1.53194\n",
      "              Coef_price  : 0.09152912\n",
      "\n",
      "              R. intercept: 0.00131\n",
      "              Coef        : -0.00000249\n",
      "\n",
      "              Target_sell : 16.06\n",
      "              Actual_price: 15.45\n",
      "              Target_buy  : 14.64\n",
      "\n",
      "              Base_price  : 6.96\n",
      "              Stop_loss   : -54.96%\n",
      "\n",
      "              Stock_return: 21.37%\n",
      "\n",
      "\n",
      "===========> LWSA3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  135\n",
      "              Negative -  108\n",
      "              Pct Up   - 55.56\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  10\n",
      "              Negative -  2\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.656\n",
      "\n",
      "              R. price    : 3.55439\n",
      "              Coef_price  : 0.09668398\n",
      "\n",
      "              R. intercept: 0.01419\n",
      "              Coef        : -0.00005513\n",
      "\n",
      "              Target_sell : 25.30\n",
      "              Actual_price: 23.00\n",
      "              Target_buy  : 22.98\n",
      "\n",
      "              Base_price  : 13.28\n",
      "              Stop_loss   : -42.27%\n",
      "\n",
      "              Stock_return: 405.49%\n",
      "\n",
      "\n",
      "===========> MDIA3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  116\n",
      "              Negative -  127\n",
      "              Pct Up   - 47.74\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  6\n",
      "              Negative -  6\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.875\n",
      "\n",
      "              R. price    : 36.82279\n",
      "              Coef_price  : -0.02133800\n",
      "\n",
      "              R. intercept: 0.00295\n",
      "              Coef        : -0.00002270\n",
      "\n",
      "              Target_sell : 30.61\n",
      "              Actual_price: 30.56\n",
      "              Target_buy  : 31.27\n",
      "\n",
      "              Base_price  : 33.69\n",
      "              Stop_loss   : 10.25%\n",
      "\n",
      "              Stock_return: -1.16%\n",
      "\n",
      "\n",
      "===========> MEAL3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  120\n",
      "              Negative -  123\n",
      "              Pct Up   - 49.38\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  6\n",
      "              Negative -  6\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -4.475\n",
      "\n",
      "              R. price    : 3.57972\n",
      "              Coef_price  : 0.00071494\n",
      "\n",
      "              R. intercept: 0.00349\n",
      "              Coef        : -0.00001816\n",
      "\n",
      "              Target_sell : 3.55\n",
      "              Actual_price: 3.53\n",
      "              Target_buy  : 3.55\n",
      "\n",
      "              Base_price  : 3.55\n",
      "              Stop_loss   : 0.70%\n",
      "\n",
      "              Stock_return: 6.33%\n",
      "\n",
      "\n",
      "===========> MGLU3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  126\n",
      "              Negative -  117\n",
      "              Pct Up   - 51.85\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.275\n",
      "\n",
      "              R. price    : 13.93581\n",
      "              Coef_price  : 0.05562655\n",
      "\n",
      "              R. intercept: 0.01185\n",
      "              Coef        : -0.00007103\n",
      "\n",
      "              Target_sell : 22.01\n",
      "              Actual_price: 19.97\n",
      "              Target_buy  : 20.85\n",
      "\n",
      "              Base_price  : 16.95\n",
      "              Stop_loss   : -15.11%\n",
      "\n",
      "              Stock_return: 97.33%\n",
      "\n",
      "\n",
      "===========> MILS3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  123\n",
      "              Negative -  120\n",
      "              Pct Up   - 50.62\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  5\n",
      "              Negative -  7\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -1.850\n",
      "\n",
      "              R. price    : 5.57634\n",
      "              Coef_price  : 0.00345626\n",
      "\n",
      "              R. intercept: 0.00605\n",
      "              Coef        : -0.00002773\n",
      "\n",
      "              Target_sell : 6.42\n",
      "              Actual_price: 6.66\n",
      "              Target_buy  : 6.39\n",
      "\n",
      "              Base_price  : 6.12\n",
      "              Stop_loss   : -8.14%\n",
      "\n",
      "              Stock_return: 58.57%\n",
      "\n",
      "\n",
      "===========> MRFG3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  125\n",
      "              Negative -  118\n",
      "              Pct Up   - 51.44\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.266\n",
      "\n",
      "              R. price    : 12.43570\n",
      "              Coef_price  : 0.01329483\n",
      "\n",
      "              R. intercept: 0.00631\n",
      "              Coef        : -0.00002788\n",
      "\n",
      "              Target_sell : 16.76\n",
      "              Actual_price: 16.84\n",
      "              Target_buy  : 16.54\n",
      "\n",
      "              Base_price  : 14.64\n",
      "              Stop_loss   : -13.08%\n",
      "\n",
      "              Stock_return: 88.16%\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "===========> MYPK3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  118\n",
      "              Negative -  125\n",
      "              Pct Up   - 48.56\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -1.979\n",
      "\n",
      "              R. price    : 12.94591\n",
      "              Coef_price  : 0.00447712\n",
      "\n",
      "              R. intercept: 0.00542\n",
      "              Coef        : -0.00003732\n",
      "\n",
      "              Target_sell : 12.14\n",
      "              Actual_price: 11.84\n",
      "              Target_buy  : 12.09\n",
      "\n",
      "              Base_price  : 12.39\n",
      "              Stop_loss   : 4.67%\n",
      "\n",
      "              Stock_return: 7.83%\n",
      "\n",
      "\n",
      "===========> NEOE3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  120\n",
      "              Negative -  123\n",
      "              Pct Up   - 49.38\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  4\n",
      "              Negative -  8\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -1.901\n",
      "\n",
      "              R. price    : 18.67005\n",
      "              Coef_price  : -0.00524427\n",
      "\n",
      "              R. intercept: 0.00234\n",
      "              Coef        : -0.00001697\n",
      "\n",
      "              Target_sell : 16.47\n",
      "              Actual_price: 16.71\n",
      "              Target_buy  : 16.56\n",
      "\n",
      "              Base_price  : 17.69\n",
      "              Stop_loss   : 5.86%\n",
      "\n",
      "              Stock_return: 0.12%\n",
      "\n",
      "\n",
      "===========> NGRD3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  34\n",
      "              Negative -  26\n",
      "              Pct Up   - 56.67\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  2\n",
      "              Negative -  1\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 1.656\n",
      "\n",
      "              R. price    : -2.51084\n",
      "              Coef_price  : 0.03754214\n",
      "\n",
      "              R. intercept: -0.00112\n",
      "              Coef        : 0.00002912\n",
      "\n",
      "              Target_sell : 8.10\n",
      "              Actual_price: 7.87\n",
      "              Target_buy  : 7.80\n",
      "\n",
      "              Base_price  : 2.68\n",
      "              Stop_loss   : -65.95%\n",
      "\n",
      "              Stock_return: 59.31%\n",
      "\n",
      "\n",
      "===========> NTCO3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  120\n",
      "              Negative -  123\n",
      "              Pct Up   - 49.38\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.869\n",
      "\n",
      "              R. price    : 35.82121\n",
      "              Coef_price  : 0.07558195\n",
      "\n",
      "              R. intercept: 0.00789\n",
      "              Coef        : -0.00004213\n",
      "\n",
      "              Target_sell : 51.56\n",
      "              Actual_price: 48.76\n",
      "              Target_buy  : 47.83\n",
      "\n",
      "              Base_price  : 42.29\n",
      "              Stop_loss   : -13.27%\n",
      "\n",
      "              Stock_return: 77.76%\n",
      "\n",
      "\n",
      "===========> ODPV3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  126\n",
      "              Negative -  117\n",
      "              Pct Up   - 51.85\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -3.560\n",
      "\n",
      "              R. price    : 13.85174\n",
      "              Coef_price  : -0.00354692\n",
      "\n",
      "              R. intercept: 0.00039\n",
      "              Coef        : -0.00000143\n",
      "\n",
      "              Target_sell : 13.01\n",
      "              Actual_price: 13.36\n",
      "              Target_buy  : 13.05\n",
      "\n",
      "              Base_price  : 13.61\n",
      "              Stop_loss   : 1.84%\n",
      "\n",
      "              Stock_return: -0.82%\n",
      "\n",
      "\n",
      "===========> OIBR3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  128\n",
      "              Negative -  115\n",
      "              Pct Up   - 52.67\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -3.943\n",
      "\n",
      "              R. price    : 0.72199\n",
      "              Coef_price  : 0.00679903\n",
      "\n",
      "              R. intercept: 0.01572\n",
      "              Coef        : -0.00007985\n",
      "\n",
      "              Target_sell : 1.83\n",
      "              Actual_price: 1.80\n",
      "              Target_buy  : 1.81\n",
      "\n",
      "              Base_price  : 1.26\n",
      "              Stop_loss   : -29.95%\n",
      "\n",
      "              Stock_return: 246.15%\n",
      "\n",
      "\n",
      "===========> OIBR4.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  121\n",
      "              Negative -  122\n",
      "              Pct Up   - 49.79\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -3.028\n",
      "\n",
      "              R. price    : 1.18550\n",
      "              Coef_price  : 0.00776119\n",
      "\n",
      "              R. intercept: 0.01207\n",
      "              Coef        : -0.00005928\n",
      "\n",
      "              Target_sell : 2.38\n",
      "              Actual_price: 2.36\n",
      "              Target_buy  : 2.36\n",
      "\n",
      "              Base_price  : 1.77\n",
      "              Stop_loss   : -24.88%\n",
      "\n",
      "              Stock_return: 145.83%\n",
      "\n",
      "\n",
      "===========> PCAR3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  134\n",
      "              Negative -  109\n",
      "              Pct Up   - 55.14\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  5\n",
      "              Negative -  7\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -1.019\n",
      "\n",
      "              R. price    : 73.09398\n",
      "              Coef_price  : -0.07643442\n",
      "\n",
      "              R. intercept: -0.00409\n",
      "              Coef        : 0.00006420\n",
      "\n",
      "              Target_sell : 27.51\n",
      "              Actual_price: 31.30\n",
      "              Target_buy  : 29.78\n",
      "\n",
      "              Base_price  : 52.20\n",
      "              Stop_loss   : 66.77%\n",
      "\n",
      "              Stock_return: -51.42%\n",
      "\n",
      "\n",
      "===========> PETR3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  130\n",
      "              Negative -  113\n",
      "              Pct Up   - 53.50\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.388\n",
      "\n",
      "              R. price    : 18.43625\n",
      "              Coef_price  : 0.03494840\n",
      "\n",
      "              R. intercept: 0.00909\n",
      "              Coef        : -0.00005062\n",
      "\n",
      "              Target_sell : 23.37\n",
      "              Actual_price: 23.25\n",
      "              Target_buy  : 22.57\n",
      "\n",
      "              Base_price  : 20.84\n",
      "              Stop_loss   : -10.35%\n",
      "\n",
      "              Stock_return: 79.68%\n",
      "\n",
      "\n",
      "===========> PETR4.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  129\n",
      "              Negative -  114\n",
      "              Pct Up   - 53.09\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  6\n",
      "              Negative -  6\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.373\n",
      "\n",
      "              R. price    : 18.04190\n",
      "              Coef_price  : 0.03568631\n",
      "\n",
      "              R. intercept: 0.00805\n",
      "              Coef        : -0.00004313\n",
      "\n",
      "              Target_sell : 23.69\n",
      "              Actual_price: 23.42\n",
      "              Target_buy  : 22.86\n",
      "\n",
      "              Base_price  : 20.73\n",
      "              Stop_loss   : -11.48%\n",
      "\n",
      "              Stock_return: 75.04%\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "===========> PETZ3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  65\n",
      "              Negative -  61\n",
      "              Pct Up   - 51.59\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  5\n",
      "              Negative -  1\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.111\n",
      "\n",
      "              R. price    : -4.87948\n",
      "              Coef_price  : 0.11997301\n",
      "\n",
      "              R. intercept: 0.00053\n",
      "              Coef        : 0.00000451\n",
      "\n",
      "              Target_sell : 21.20\n",
      "              Actual_price: 19.29\n",
      "              Target_buy  : 18.81\n",
      "\n",
      "              Base_price  : 7.21\n",
      "              Stop_loss   : -62.65%\n",
      "\n",
      "              Stock_return: 24.69%\n",
      "\n",
      "\n",
      "===========> POSI3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  121\n",
      "              Negative -  122\n",
      "              Pct Up   - 49.79\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  6\n",
      "              Negative -  6\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -2.657\n",
      "\n",
      "              R. price    : 4.29925\n",
      "              Coef_price  : 0.00316406\n",
      "\n",
      "              R. intercept: 0.00498\n",
      "              Coef        : -0.00001766\n",
      "\n",
      "              Target_sell : 5.97\n",
      "              Actual_price: 5.55\n",
      "              Target_buy  : 5.95\n",
      "\n",
      "              Base_price  : 4.92\n",
      "              Stop_loss   : -11.27%\n",
      "\n",
      "              Stock_return: 59.94%\n",
      "\n",
      "\n",
      "===========> PRIO3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  117\n",
      "              Negative -  126\n",
      "              Pct Up   - 48.15\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 1.298\n",
      "\n",
      "              R. price    : 14.44388\n",
      "              Coef_price  : 0.26862693\n",
      "\n",
      "              R. intercept: 0.01065\n",
      "              Coef        : -0.00002083\n",
      "\n",
      "              Target_sell : 102.17\n",
      "              Actual_price: 92.50\n",
      "              Target_buy  : 78.13\n",
      "\n",
      "              Base_price  : 53.47\n",
      "              Stop_loss   : -42.19%\n",
      "\n",
      "              Stock_return: 444.12%\n",
      "\n",
      "\n",
      "===========> PSSA3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  118\n",
      "              Negative -  125\n",
      "              Pct Up   - 48.56\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  5\n",
      "              Negative -  7\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.301\n",
      "\n",
      "              R. price    : 48.84669\n",
      "              Coef_price  : -0.00129241\n",
      "\n",
      "              R. intercept: 0.00254\n",
      "              Coef        : -0.00001622\n",
      "\n",
      "              Target_sell : 46.69\n",
      "              Actual_price: 47.04\n",
      "              Target_buy  : 46.75\n",
      "\n",
      "              Base_price  : 47.94\n",
      "              Stop_loss   : 1.92%\n",
      "\n",
      "              Stock_return: 8.69%\n",
      "\n",
      "\n",
      "===========> PTBL3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  129\n",
      "              Negative -  114\n",
      "              Pct Up   - 53.09\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  10\n",
      "              Negative -  2\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.063\n",
      "\n",
      "              R. price    : 2.00809\n",
      "              Coef_price  : 0.02908862\n",
      "\n",
      "              R. intercept: 0.01068\n",
      "              Coef        : -0.00003506\n",
      "\n",
      "              Target_sell : 9.33\n",
      "              Actual_price: 8.61\n",
      "              Target_buy  : 9.07\n",
      "\n",
      "              Base_price  : 5.31\n",
      "              Stop_loss   : -38.34%\n",
      "\n",
      "              Stock_return: 280.97%\n",
      "\n",
      "\n",
      "===========> QUAL3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  123\n",
      "              Negative -  120\n",
      "              Pct Up   - 50.62\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  6\n",
      "              Negative -  6\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.059\n",
      "\n",
      "              R. price    : 24.70112\n",
      "              Coef_price  : 0.04284798\n",
      "\n",
      "              R. intercept: 0.00398\n",
      "              Coef        : -0.00002069\n",
      "\n",
      "              Target_sell : 33.01\n",
      "              Actual_price: 31.11\n",
      "              Target_buy  : 31.64\n",
      "\n",
      "              Base_price  : 27.91\n",
      "              Stop_loss   : -10.30%\n",
      "\n",
      "              Stock_return: 30.33%\n",
      "\n",
      "\n",
      "===========> RADL3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  124\n",
      "              Negative -  119\n",
      "              Pct Up   - 51.03\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.577\n",
      "\n",
      "              R. price    : 20.98347\n",
      "              Coef_price  : 0.01926495\n",
      "\n",
      "              R. intercept: 0.00171\n",
      "              Coef        : -0.00000600\n",
      "\n",
      "              Target_sell : 25.69\n",
      "              Actual_price: 24.85\n",
      "              Target_buy  : 25.20\n",
      "\n",
      "              Base_price  : 22.92\n",
      "              Stop_loss   : -7.78%\n",
      "\n",
      "              Stock_return: 19.76%\n",
      "\n",
      "\n",
      "===========> RAIL3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  117\n",
      "              Negative -  126\n",
      "              Pct Up   - 48.15\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  6\n",
      "              Negative -  6\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -1.674\n",
      "\n",
      "              R. price    : 22.08635\n",
      "              Coef_price  : -0.01190748\n",
      "\n",
      "              R. intercept: 0.00132\n",
      "              Coef        : -0.00000838\n",
      "\n",
      "              Target_sell : 19.86\n",
      "              Actual_price: 19.75\n",
      "              Target_buy  : 20.09\n",
      "\n",
      "              Base_price  : 20.92\n",
      "              Stop_loss   : 5.91%\n",
      "\n",
      "              Stock_return: -0.25%\n",
      "\n",
      "\n",
      "===========> RANI3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  131\n",
      "              Negative -  112\n",
      "              Pct Up   - 53.91\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -1.639\n",
      "\n",
      "              R. price    : 3.26598\n",
      "              Coef_price  : 0.01137653\n",
      "\n",
      "              R. intercept: 0.00873\n",
      "              Coef        : -0.00004010\n",
      "\n",
      "              Target_sell : 5.69\n",
      "              Actual_price: 5.60\n",
      "              Target_buy  : 5.63\n",
      "\n",
      "              Base_price  : 4.43\n",
      "              Stop_loss   : -20.84%\n",
      "\n",
      "              Stock_return: 104.38%\n",
      "\n",
      "\n",
      "===========> RCSL4.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  134\n",
      "              Negative -  109\n",
      "              Pct Up   - 55.14\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -9.381\n",
      "\n",
      "              R. price    : 1.54460\n",
      "              Coef_price  : -0.00004506\n",
      "\n",
      "              R. intercept: 0.01004\n",
      "              Coef        : -0.00005971\n",
      "\n",
      "              Target_sell : 1.38\n",
      "              Actual_price: 1.40\n",
      "              Target_buy  : 1.38\n",
      "\n",
      "              Base_price  : 1.47\n",
      "              Stop_loss   : 5.16%\n",
      "\n",
      "              Stock_return: 48.94%\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "===========> SANB11.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  120\n",
      "              Negative -  123\n",
      "              Pct Up   - 49.38\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.406\n",
      "\n",
      "              R. price    : 22.95989\n",
      "              Coef_price  : 0.07983533\n",
      "\n",
      "              R. intercept: 0.00130\n",
      "              Coef        : 0.00000609\n",
      "\n",
      "              Target_sell : 41.38\n",
      "              Actual_price: 40.94\n",
      "              Target_buy  : 38.21\n",
      "\n",
      "              Base_price  : 31.95\n",
      "              Stop_loss   : -21.96%\n",
      "\n",
      "              Stock_return: 48.49%\n",
      "\n",
      "\n",
      "===========> SEER3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  116\n",
      "              Negative -  127\n",
      "              Pct Up   - 47.74\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  5\n",
      "              Negative -  7\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -3.397\n",
      "\n",
      "              R. price    : 15.96121\n",
      "              Coef_price  : -0.01137690\n",
      "\n",
      "              R. intercept: 0.00172\n",
      "              Coef        : -0.00001961\n",
      "\n",
      "              Target_sell : 11.71\n",
      "              Actual_price: 11.50\n",
      "              Target_buy  : 11.84\n",
      "\n",
      "              Base_price  : 13.73\n",
      "              Stop_loss   : 19.40%\n",
      "\n",
      "              Stock_return: -27.90%\n",
      "\n",
      "\n",
      "===========> SLCE3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  129\n",
      "              Negative -  114\n",
      "              Pct Up   - 53.09\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  9\n",
      "              Negative -  3\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.950\n",
      "\n",
      "              R. price    : 18.87178\n",
      "              Coef_price  : 0.07103898\n",
      "\n",
      "              R. intercept: 0.00056\n",
      "              Coef        : 0.00002057\n",
      "\n",
      "              Target_sell : 42.83\n",
      "              Actual_price: 42.47\n",
      "              Target_buy  : 39.88\n",
      "\n",
      "              Base_price  : 30.67\n",
      "              Stop_loss   : -27.78%\n",
      "\n",
      "              Stock_return: 99.48%\n",
      "\n",
      "\n",
      "===========> SMLS3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  129\n",
      "              Negative -  114\n",
      "              Pct Up   - 53.09\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.734\n",
      "\n",
      "              R. price    : 9.51893\n",
      "              Coef_price  : 0.05638248\n",
      "\n",
      "              R. intercept: 0.00536\n",
      "              Coef        : -0.00000692\n",
      "\n",
      "              Target_sell : 24.33\n",
      "              Actual_price: 24.80\n",
      "              Target_buy  : 22.97\n",
      "\n",
      "              Base_price  : 17.16\n",
      "              Stop_loss   : -30.81%\n",
      "\n",
      "              Stock_return: 145.54%\n",
      "\n",
      "\n",
      "===========> SMTO3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  132\n",
      "              Negative -  111\n",
      "              Pct Up   - 54.32\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.581\n",
      "\n",
      "              R. price    : 16.13147\n",
      "              Coef_price  : 0.06063467\n",
      "\n",
      "              R. intercept: 0.00531\n",
      "              Coef        : -0.00001959\n",
      "\n",
      "              Target_sell : 30.52\n",
      "              Actual_price: 28.91\n",
      "              Target_buy  : 28.75\n",
      "\n",
      "              Base_price  : 22.52\n",
      "              Stop_loss   : -22.10%\n",
      "\n",
      "              Stock_return: 87.73%\n",
      "\n",
      "\n",
      "===========> SOMA3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  84\n",
      "              Negative -  74\n",
      "              Pct Up   - 53.16\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  5\n",
      "              Negative -  3\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.467\n",
      "\n",
      "              R. price    : -1.26431\n",
      "              Coef_price  : 0.07542043\n",
      "\n",
      "              R. intercept: -0.00049\n",
      "              Coef        : 0.00001387\n",
      "\n",
      "              Target_sell : 14.67\n",
      "              Actual_price: 14.00\n",
      "              Target_buy  : 13.60\n",
      "\n",
      "              Base_price  : 6.37\n",
      "              Stop_loss   : -54.52%\n",
      "\n",
      "              Stock_return: 26.93%\n",
      "\n",
      "\n",
      "===========> STBP3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  130\n",
      "              Negative -  113\n",
      "              Pct Up   - 53.50\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  6\n",
      "              Negative -  6\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -2.249\n",
      "\n",
      "              R. price    : 4.29979\n",
      "              Coef_price  : 0.00651692\n",
      "\n",
      "              R. intercept: -0.00084\n",
      "              Coef        : 0.00002253\n",
      "\n",
      "              Target_sell : 6.75\n",
      "              Actual_price: 6.76\n",
      "              Target_buy  : 6.71\n",
      "\n",
      "              Base_price  : 5.53\n",
      "              Stop_loss   : -18.20%\n",
      "\n",
      "              Stock_return: 40.25%\n",
      "\n",
      "\n",
      "===========> SUZB3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  126\n",
      "              Negative -  117\n",
      "              Pct Up   - 51.85\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  9\n",
      "              Negative -  3\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 1.110\n",
      "\n",
      "              R. price    : 32.43217\n",
      "              Coef_price  : 0.14746832\n",
      "\n",
      "              R. intercept: 0.00350\n",
      "              Coef        : -0.00000025\n",
      "\n",
      "              Target_sell : 78.59\n",
      "              Actual_price: 72.50\n",
      "              Target_buy  : 67.87\n",
      "\n",
      "              Base_price  : 52.47\n",
      "              Stop_loss   : -27.63%\n",
      "\n",
      "              Stock_return: 113.30%\n",
      "\n",
      "\n",
      "===========> TAEE11.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  125\n",
      "              Negative -  117\n",
      "              Pct Up   - 51.65\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.821\n",
      "\n",
      "              R. price    : 23.83610\n",
      "              Coef_price  : 0.03779511\n",
      "\n",
      "              R. intercept: 0.00184\n",
      "              Coef        : 0.00000105\n",
      "\n",
      "              Target_sell : 36.36\n",
      "              Actual_price: 36.10\n",
      "              Target_buy  : 35.00\n",
      "\n",
      "              Base_price  : 29.97\n",
      "              Stop_loss   : -16.99%\n",
      "\n",
      "              Stock_return: 58.89%\n",
      "\n",
      "\n",
      "===========> TASA4.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  128\n",
      "              Negative -  115\n",
      "              Pct Up   - 52.67\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  10\n",
      "              Negative -  2\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.826\n",
      "\n",
      "              R. price    : 0.81091\n",
      "              Coef_price  : 0.07731338\n",
      "\n",
      "              R. intercept: 0.00628\n",
      "              Coef        : 0.00001612\n",
      "\n",
      "              Target_sell : 24.28\n",
      "              Actual_price: 22.72\n",
      "              Target_buy  : 22.51\n",
      "\n",
      "              Base_price  : 11.77\n",
      "              Stop_loss   : -48.22%\n",
      "\n",
      "              Stock_return: 475.19%\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "===========> TIET11.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  128\n",
      "              Negative -  114\n",
      "              Pct Up   - 52.89\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.665\n",
      "\n",
      "              R. price    : 13.48311\n",
      "              Coef_price  : 0.01215551\n",
      "\n",
      "              R. intercept: 0.00183\n",
      "              Coef        : -0.00000300\n",
      "\n",
      "              Target_sell : 17.27\n",
      "              Actual_price: 17.44\n",
      "              Target_buy  : 17.07\n",
      "\n",
      "              Base_price  : 15.46\n",
      "              Stop_loss   : -11.34%\n",
      "\n",
      "              Stock_return: 36.14%\n",
      "\n",
      "\n",
      "===========> TOTS3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  136\n",
      "              Negative -  107\n",
      "              Pct Up   - 55.97\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -1.501\n",
      "\n",
      "              R. price    : 27.13125\n",
      "              Coef_price  : 0.00388674\n",
      "\n",
      "              R. intercept: -0.00219\n",
      "              Coef        : 0.00001893\n",
      "\n",
      "              Target_sell : 28.64\n",
      "              Actual_price: 28.22\n",
      "              Target_buy  : 28.53\n",
      "\n",
      "              Base_price  : 27.68\n",
      "              Stop_loss   : -1.93%\n",
      "\n",
      "              Stock_return: -39.38%\n",
      "\n",
      "\n",
      "===========> TRPL4.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  124\n",
      "              Negative -  119\n",
      "              Pct Up   - 51.03\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.189\n",
      "\n",
      "              R. price    : 16.61203\n",
      "              Coef_price  : 0.04008503\n",
      "\n",
      "              R. intercept: 0.00198\n",
      "              Coef        : -0.00000238\n",
      "\n",
      "              Target_sell : 25.32\n",
      "              Actual_price: 25.59\n",
      "              Target_buy  : 24.33\n",
      "\n",
      "              Base_price  : 21.10\n",
      "              Stop_loss   : -17.54%\n",
      "\n",
      "              Stock_return: 47.15%\n",
      "\n",
      "\n",
      "===========> USIM5.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  126\n",
      "              Negative -  117\n",
      "              Pct Up   - 51.85\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  10\n",
      "              Negative -  2\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.534\n",
      "\n",
      "              R. price    : 3.81597\n",
      "              Coef_price  : 0.05376106\n",
      "\n",
      "              R. intercept: 0.00797\n",
      "              Coef        : -0.00001808\n",
      "\n",
      "              Target_sell : 17.42\n",
      "              Actual_price: 16.58\n",
      "              Target_buy  : 16.53\n",
      "\n",
      "              Base_price  : 10.20\n",
      "              Stop_loss   : -38.49%\n",
      "\n",
      "              Stock_return: 249.79%\n",
      "\n",
      "\n",
      "===========> VALE3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  127\n",
      "              Negative -  116\n",
      "              Pct Up   - 52.26\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 1.130\n",
      "\n",
      "              R. price    : 34.85782\n",
      "              Coef_price  : 0.23964781\n",
      "\n",
      "              R. intercept: 0.00454\n",
      "              Coef        : -0.00000462\n",
      "\n",
      "              Target_sell : 105.07\n",
      "              Actual_price: 95.53\n",
      "              Target_buy  : 82.76\n",
      "\n",
      "              Base_price  : 65.19\n",
      "              Stop_loss   : -31.76%\n",
      "\n",
      "              Stock_return: 148.97%\n",
      "\n",
      "\n",
      "===========> VVAR3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  126\n",
      "              Negative -  117\n",
      "              Pct Up   - 51.85\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  5\n",
      "              Negative -  7\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.017\n",
      "\n",
      "              R. price    : 13.03549\n",
      "              Coef_price  : 0.01697142\n",
      "\n",
      "              R. intercept: 0.01910\n",
      "              Coef        : -0.00012316\n",
      "\n",
      "              Target_sell : 12.05\n",
      "              Actual_price: 11.96\n",
      "              Target_buy  : 11.85\n",
      "\n",
      "              Base_price  : 12.50\n",
      "              Stop_loss   : 4.49%\n",
      "\n",
      "              Stock_return: 119.45%\n",
      "\n",
      "\n",
      "===========> WEGE3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  133\n",
      "              Negative -  110\n",
      "              Pct Up   - 54.73\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.805\n",
      "\n",
      "              R. price    : 39.71851\n",
      "              Coef_price  : 0.20173651\n",
      "\n",
      "              R. intercept: 0.00913\n",
      "              Coef        : -0.00004600\n",
      "\n",
      "              Target_sell : 78.98\n",
      "              Actual_price: 72.97\n",
      "              Target_buy  : 64.57\n",
      "\n",
      "              Base_price  : 56.34\n",
      "              Stop_loss   : -22.79%\n",
      "\n",
      "              Stock_return: 116.34%\n",
      "\n",
      "\n",
      "===========> YDUQ3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  114\n",
      "              Negative -  129\n",
      "              Pct Up   - 46.91\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  5\n",
      "              Negative -  7\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -0.638\n",
      "\n",
      "              R. price    : 29.53500\n",
      "              Coef_price  : 0.00589346\n",
      "\n",
      "              R. intercept: 0.00444\n",
      "              Coef        : -0.00002989\n",
      "\n",
      "              Target_sell : 27.47\n",
      "              Actual_price: 27.09\n",
      "              Target_buy  : 27.31\n",
      "\n",
      "              Base_price  : 28.31\n",
      "              Stop_loss   : 4.51%\n",
      "\n",
      "              Stock_return: 3.12%\n",
      "\n"
     ]
    }
   ],
   "source": [
    "best_names = stocks_all['Adj Close'].columns\n",
    "finals_stocks = routine(best_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 380,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Reg_price</th>\n",
       "      <th>Coef_price</th>\n",
       "      <th>Reg_int</th>\n",
       "      <th>Coef_int</th>\n",
       "      <th>Rel_price_ret</th>\n",
       "      <th>Pct_up_day</th>\n",
       "      <th>Pct_up_month</th>\n",
       "      <th>Sharpe</th>\n",
       "      <th>Base_price</th>\n",
       "      <th>Target_buy</th>\n",
       "      <th>Target_sell</th>\n",
       "      <th>Actual_price</th>\n",
       "      <th>Ret_real</th>\n",
       "      <th>Stop_loss</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ABEV3.SA</th>\n",
       "      <td>12.0936</td>\n",
       "      <td>0.0134759</td>\n",
       "      <td>0.00110923</td>\n",
       "      <td>-3.33518e-07</td>\n",
       "      <td>-40405.2</td>\n",
       "      <td>51.8519</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.20764</td>\n",
       "      <td>12.0936</td>\n",
       "      <td>15.0657</td>\n",
       "      <td>15.2693</td>\n",
       "      <td>15.15</td>\n",
       "      <td>21.297</td>\n",
       "      <td>-10.0871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AERI3.SA</th>\n",
       "      <td>-3.25147</td>\n",
       "      <td>0.0545038</td>\n",
       "      <td>0.000277664</td>\n",
       "      <td>1.33361e-05</td>\n",
       "      <td>4086.95</td>\n",
       "      <td>48.8372</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.361511</td>\n",
       "      <td>-3.25151</td>\n",
       "      <td>9.00168</td>\n",
       "      <td>9.49943</td>\n",
       "      <td>9.1</td>\n",
       "      <td>49.1803</td>\n",
       "      <td>-67.8654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALPA4.SA</th>\n",
       "      <td>26.5389</td>\n",
       "      <td>0.0645494</td>\n",
       "      <td>0.00536622</td>\n",
       "      <td>-2.72935e-05</td>\n",
       "      <td>-2365.01</td>\n",
       "      <td>52.6749</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.392118</td>\n",
       "      <td>26.5382</td>\n",
       "      <td>34.7423</td>\n",
       "      <td>37.0637</td>\n",
       "      <td>36.69</td>\n",
       "      <td>50.6158</td>\n",
       "      <td>-13.8345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ANIM3.SA</th>\n",
       "      <td>25.4991</td>\n",
       "      <td>0.000280565</td>\n",
       "      <td>0.0086771</td>\n",
       "      <td>-7.94031e-05</td>\n",
       "      <td>-3.53343</td>\n",
       "      <td>50.2058</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.924437</td>\n",
       "      <td>25.4971</td>\n",
       "      <td>8.94107</td>\n",
       "      <td>8.94293</td>\n",
       "      <td>9.13</td>\n",
       "      <td>-56.2739</td>\n",
       "      <td>89.6334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AZUL4.SA</th>\n",
       "      <td>12.5214</td>\n",
       "      <td>0.12242</td>\n",
       "      <td>0.00452644</td>\n",
       "      <td>-4.19975e-06</td>\n",
       "      <td>-29149.4</td>\n",
       "      <td>51.0288</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.507608</td>\n",
       "      <td>12.5214</td>\n",
       "      <td>36.1776</td>\n",
       "      <td>40.7654</td>\n",
       "      <td>37.47</td>\n",
       "      <td>96.2808</td>\n",
       "      <td>-33.2915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BEEF3.SA</th>\n",
       "      <td>12.6667</td>\n",
       "      <td>-0.0127695</td>\n",
       "      <td>0.0075359</td>\n",
       "      <td>-5.05503e-05</td>\n",
       "      <td>252.61</td>\n",
       "      <td>47.3251</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.13087</td>\n",
       "      <td>12.666</td>\n",
       "      <td>9.93421</td>\n",
       "      <td>9.80679</td>\n",
       "      <td>9.83</td>\n",
       "      <td>29.0026</td>\n",
       "      <td>14.4253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BIDI4.SA</th>\n",
       "      <td>3.33513</td>\n",
       "      <td>0.17122</td>\n",
       "      <td>0.00454223</td>\n",
       "      <td>2.17822e-05</td>\n",
       "      <td>7860.55</td>\n",
       "      <td>57.0248</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.00022</td>\n",
       "      <td>3.33521</td>\n",
       "      <td>47.3659</td>\n",
       "      <td>56.3313</td>\n",
       "      <td>50.98</td>\n",
       "      <td>373.792</td>\n",
       "      <td>-46.7289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BKBR3.SA</th>\n",
       "      <td>10.7676</td>\n",
       "      <td>-0.00250519</td>\n",
       "      <td>0.00375005</td>\n",
       "      <td>-2.54677e-05</td>\n",
       "      <td>98.3671</td>\n",
       "      <td>50.8264</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-2.51257</td>\n",
       "      <td>10.7673</td>\n",
       "      <td>9.34298</td>\n",
       "      <td>9.31924</td>\n",
       "      <td>9.48</td>\n",
       "      <td>-0.732984</td>\n",
       "      <td>6.78965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BMGB4.SA</th>\n",
       "      <td>4.65172</td>\n",
       "      <td>0.00232217</td>\n",
       "      <td>0.00522117</td>\n",
       "      <td>-2.79742e-05</td>\n",
       "      <td>-83.0111</td>\n",
       "      <td>49.5868</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-4.51686</td>\n",
       "      <td>4.65159</td>\n",
       "      <td>5.13533</td>\n",
       "      <td>5.14717</td>\n",
       "      <td>5.15</td>\n",
       "      <td>41.0959</td>\n",
       "      <td>-4.83898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BPAN4.SA</th>\n",
       "      <td>-24.7194</td>\n",
       "      <td>0.470072</td>\n",
       "      <td>-2.45786</td>\n",
       "      <td>0.036099</td>\n",
       "      <td>13.0218</td>\n",
       "      <td>49.3827</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.00222517</td>\n",
       "      <td>-25.6118</td>\n",
       "      <td>8.23559</td>\n",
       "      <td>13.7464</td>\n",
       "      <td>10.78</td>\n",
       "      <td>115.6</td>\n",
       "      <td>-168.793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BRAP4.SA</th>\n",
       "      <td>25.1743</td>\n",
       "      <td>0.179678</td>\n",
       "      <td>0.00554649</td>\n",
       "      <td>-1.40092e-05</td>\n",
       "      <td>-12825.7</td>\n",
       "      <td>52.6749</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.929584</td>\n",
       "      <td>25.1739</td>\n",
       "      <td>57.1956</td>\n",
       "      <td>68.4134</td>\n",
       "      <td>65.37</td>\n",
       "      <td>138.577</td>\n",
       "      <td>-30.745</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BRFS3.SA</th>\n",
       "      <td>19.5264</td>\n",
       "      <td>0.0103121</td>\n",
       "      <td>0.00526307</td>\n",
       "      <td>-2.22366e-05</td>\n",
       "      <td>-463.747</td>\n",
       "      <td>46.0905</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.65336</td>\n",
       "      <td>19.5259</td>\n",
       "      <td>24.4675</td>\n",
       "      <td>24.7195</td>\n",
       "      <td>24.39</td>\n",
       "      <td>68.091</td>\n",
       "      <td>-9.97144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BRKM5.SA</th>\n",
       "      <td>20.5091</td>\n",
       "      <td>0.0315566</td>\n",
       "      <td>0.00275021</td>\n",
       "      <td>8.25936e-06</td>\n",
       "      <td>3820.71</td>\n",
       "      <td>50.2058</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.35737</td>\n",
       "      <td>20.5093</td>\n",
       "      <td>36.5271</td>\n",
       "      <td>37.7049</td>\n",
       "      <td>37.83</td>\n",
       "      <td>113.729</td>\n",
       "      <td>-22.8928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BTOW3.SA</th>\n",
       "      <td>97.2179</td>\n",
       "      <td>-0.0751727</td>\n",
       "      <td>0.013038</td>\n",
       "      <td>-9.53383e-05</td>\n",
       "      <td>788.484</td>\n",
       "      <td>43.6214</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0380775</td>\n",
       "      <td>97.2086</td>\n",
       "      <td>64.1091</td>\n",
       "      <td>59.5009</td>\n",
       "      <td>59.36</td>\n",
       "      <td>16.415</td>\n",
       "      <td>31.8806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAML3.SA</th>\n",
       "      <td>10.0324</td>\n",
       "      <td>0.00816934</td>\n",
       "      <td>0.00641996</td>\n",
       "      <td>-4.1261e-05</td>\n",
       "      <td>-197.992</td>\n",
       "      <td>51.8519</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.1165</td>\n",
       "      <td>10.032</td>\n",
       "      <td>10.4959</td>\n",
       "      <td>10.5811</td>\n",
       "      <td>10.29</td>\n",
       "      <td>32.2622</td>\n",
       "      <td>-1.2535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CASH3.SA</th>\n",
       "      <td>-7.91209</td>\n",
       "      <td>0.126662</td>\n",
       "      <td>-0.00154386</td>\n",
       "      <td>4.82234e-05</td>\n",
       "      <td>2626.57</td>\n",
       "      <td>57.3034</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.57223</td>\n",
       "      <td>-7.91247</td>\n",
       "      <td>22.2675</td>\n",
       "      <td>25.2234</td>\n",
       "      <td>23.02</td>\n",
       "      <td>142.571</td>\n",
       "      <td>-67.1861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CEAB3.SA</th>\n",
       "      <td>9.43923</td>\n",
       "      <td>0.0142248</td>\n",
       "      <td>0.00921757</td>\n",
       "      <td>-5.37877e-05</td>\n",
       "      <td>-264.462</td>\n",
       "      <td>48.7603</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.628457</td>\n",
       "      <td>9.43872</td>\n",
       "      <td>11.0605</td>\n",
       "      <td>11.2197</td>\n",
       "      <td>11</td>\n",
       "      <td>54.9296</td>\n",
       "      <td>-7.09674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CIEL3.SA</th>\n",
       "      <td>4.64331</td>\n",
       "      <td>-0.00444485</td>\n",
       "      <td>-6.18874e-05</td>\n",
       "      <td>-2.07368e-06</td>\n",
       "      <td>2143.46</td>\n",
       "      <td>45.679</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-5.58283</td>\n",
       "      <td>4.6433</td>\n",
       "      <td>3.62859</td>\n",
       "      <td>3.61241</td>\n",
       "      <td>3.63</td>\n",
       "      <td>-22.5071</td>\n",
       "      <td>13.9572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CNTO3.SA</th>\n",
       "      <td>30.2215</td>\n",
       "      <td>-0.0223778</td>\n",
       "      <td>0.00234068</td>\n",
       "      <td>-1.24743e-05</td>\n",
       "      <td>1793.9</td>\n",
       "      <td>42.3868</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.767965</td>\n",
       "      <td>30.2211</td>\n",
       "      <td>26.2378</td>\n",
       "      <td>25.6432</td>\n",
       "      <td>26.69</td>\n",
       "      <td>2.02599</td>\n",
       "      <td>6.6151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COGN3.SA</th>\n",
       "      <td>6.48579</td>\n",
       "      <td>-0.00881663</td>\n",
       "      <td>0.00497961</td>\n",
       "      <td>-4.29593e-05</td>\n",
       "      <td>205.232</td>\n",
       "      <td>44.856</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-2.41357</td>\n",
       "      <td>6.48551</td>\n",
       "      <td>3.99247</td>\n",
       "      <td>3.95753</td>\n",
       "      <td>3.84</td>\n",
       "      <td>-24.1107</td>\n",
       "      <td>34.4468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CPFE3.SA</th>\n",
       "      <td>27.6049</td>\n",
       "      <td>0.0149983</td>\n",
       "      <td>0.0034692</td>\n",
       "      <td>-1.88413e-05</td>\n",
       "      <td>-796.034</td>\n",
       "      <td>53.0864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0845844</td>\n",
       "      <td>27.6043</td>\n",
       "      <td>30.392</td>\n",
       "      <td>30.85</td>\n",
       "      <td>30.27</td>\n",
       "      <td>26.125</td>\n",
       "      <td>-4.40314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CPLE3.SA</th>\n",
       "      <td>64.5424</td>\n",
       "      <td>-0.0651866</td>\n",
       "      <td>0.00621486</td>\n",
       "      <td>-7.36987e-05</td>\n",
       "      <td>884.502</td>\n",
       "      <td>50.2058</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.60046</td>\n",
       "      <td>64.5376</td>\n",
       "      <td>6.94262</td>\n",
       "      <td>6.50238</td>\n",
       "      <td>6.71</td>\n",
       "      <td>-88.3689</td>\n",
       "      <td>430.906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CPLE6.SA</th>\n",
       "      <td>66.1425</td>\n",
       "      <td>-0.0574806</td>\n",
       "      <td>0.00856916</td>\n",
       "      <td>-8.7937e-05</td>\n",
       "      <td>653.656</td>\n",
       "      <td>50.2058</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.35899</td>\n",
       "      <td>66.1367</td>\n",
       "      <td>7.15613</td>\n",
       "      <td>6.75487</td>\n",
       "      <td>6.98</td>\n",
       "      <td>-86.6027</td>\n",
       "      <td>423.758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CRFB3.SA</th>\n",
       "      <td>19.7282</td>\n",
       "      <td>-0.000611192</td>\n",
       "      <td>-0.00199708</td>\n",
       "      <td>1.96037e-05</td>\n",
       "      <td>-31.1774</td>\n",
       "      <td>50.2058</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-2.43295</td>\n",
       "      <td>19.7285</td>\n",
       "      <td>20.4577</td>\n",
       "      <td>20.4453</td>\n",
       "      <td>22.22</td>\n",
       "      <td>4.31925</td>\n",
       "      <td>-5.60634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CSAN3.SA</th>\n",
       "      <td>61.7635</td>\n",
       "      <td>0.100612</td>\n",
       "      <td>0.00361612</td>\n",
       "      <td>-9.43501e-06</td>\n",
       "      <td>-10663.7</td>\n",
       "      <td>48.5597</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.16279</td>\n",
       "      <td>61.7629</td>\n",
       "      <td>87.2616</td>\n",
       "      <td>96.4824</td>\n",
       "      <td>90.8</td>\n",
       "      <td>66.8504</td>\n",
       "      <td>-15.9896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CSNA3.SA</th>\n",
       "      <td>3.14434</td>\n",
       "      <td>0.134283</td>\n",
       "      <td>0.0095891</td>\n",
       "      <td>-1.8766e-05</td>\n",
       "      <td>-7155.66</td>\n",
       "      <td>53.4979</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.875142</td>\n",
       "      <td>3.14428</td>\n",
       "      <td>32.427</td>\n",
       "      <td>37.003</td>\n",
       "      <td>35.14</td>\n",
       "      <td>398.44</td>\n",
       "      <td>-45.5261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DMMO3.SA</th>\n",
       "      <td>1.37671</td>\n",
       "      <td>-0.00127478</td>\n",
       "      <td>0.0182128</td>\n",
       "      <td>-0.000120472</td>\n",
       "      <td>10.5816</td>\n",
       "      <td>46.0905</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-10.9499</td>\n",
       "      <td>1.37654</td>\n",
       "      <td>0.883112</td>\n",
       "      <td>0.881888</td>\n",
       "      <td>0.87</td>\n",
       "      <td>35.9375</td>\n",
       "      <td>29.1115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DTEX3.SA</th>\n",
       "      <td>10.0165</td>\n",
       "      <td>0.0465516</td>\n",
       "      <td>0.00691186</td>\n",
       "      <td>-2.97199e-05</td>\n",
       "      <td>-1566.35</td>\n",
       "      <td>50.2058</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.268506</td>\n",
       "      <td>10.0162</td>\n",
       "      <td>18.7528</td>\n",
       "      <td>19.6432</td>\n",
       "      <td>18.76</td>\n",
       "      <td>95.0104</td>\n",
       "      <td>-23.3042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ELET3.SA</th>\n",
       "      <td>25.3208</td>\n",
       "      <td>0.0370729</td>\n",
       "      <td>0.00622918</td>\n",
       "      <td>-2.87828e-05</td>\n",
       "      <td>-1288.02</td>\n",
       "      <td>48.1481</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.628326</td>\n",
       "      <td>25.32</td>\n",
       "      <td>32.5352</td>\n",
       "      <td>33.7608</td>\n",
       "      <td>33.77</td>\n",
       "      <td>69.2732</td>\n",
       "      <td>-12.511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ELET6.SA</th>\n",
       "      <td>27.266</td>\n",
       "      <td>0.0286109</td>\n",
       "      <td>0.00469919</td>\n",
       "      <td>-2.10338e-05</td>\n",
       "      <td>-1360.23</td>\n",
       "      <td>49.3827</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.514253</td>\n",
       "      <td>27.2654</td>\n",
       "      <td>33.3444</td>\n",
       "      <td>34.3106</td>\n",
       "      <td>34.26</td>\n",
       "      <td>51.929</td>\n",
       "      <td>-10.2081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PETR3.SA</th>\n",
       "      <td>18.4363</td>\n",
       "      <td>0.0349484</td>\n",
       "      <td>0.0090858</td>\n",
       "      <td>-5.06246e-05</td>\n",
       "      <td>-690.344</td>\n",
       "      <td>53.4979</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.388007</td>\n",
       "      <td>18.4353</td>\n",
       "      <td>22.5714</td>\n",
       "      <td>23.3696</td>\n",
       "      <td>23.25</td>\n",
       "      <td>79.6754</td>\n",
       "      <td>-10.3541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PETR4.SA</th>\n",
       "      <td>18.0419</td>\n",
       "      <td>0.0356863</td>\n",
       "      <td>0.00804615</td>\n",
       "      <td>-4.31261e-05</td>\n",
       "      <td>-827.487</td>\n",
       "      <td>53.0864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.372988</td>\n",
       "      <td>18.0411</td>\n",
       "      <td>22.8639</td>\n",
       "      <td>23.6891</td>\n",
       "      <td>23.42</td>\n",
       "      <td>75.0374</td>\n",
       "      <td>-11.4835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PETZ3.SA</th>\n",
       "      <td>-4.87948</td>\n",
       "      <td>0.119973</td>\n",
       "      <td>0.000533084</td>\n",
       "      <td>4.50915e-06</td>\n",
       "      <td>26606.6</td>\n",
       "      <td>51.5873</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.111353</td>\n",
       "      <td>-4.87951</td>\n",
       "      <td>18.8067</td>\n",
       "      <td>21.1958</td>\n",
       "      <td>19.29</td>\n",
       "      <td>24.693</td>\n",
       "      <td>-62.6478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>POSI3.SA</th>\n",
       "      <td>4.29925</td>\n",
       "      <td>0.00316406</td>\n",
       "      <td>0.00497556</td>\n",
       "      <td>-1.76613e-05</td>\n",
       "      <td>-179.152</td>\n",
       "      <td>49.7942</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-2.65723</td>\n",
       "      <td>4.29917</td>\n",
       "      <td>5.94942</td>\n",
       "      <td>5.96858</td>\n",
       "      <td>5.55</td>\n",
       "      <td>59.9424</td>\n",
       "      <td>-11.2687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PRIO3.SA</th>\n",
       "      <td>14.4439</td>\n",
       "      <td>0.268627</td>\n",
       "      <td>0.0106452</td>\n",
       "      <td>-2.08272e-05</td>\n",
       "      <td>-12897.9</td>\n",
       "      <td>48.1481</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.29755</td>\n",
       "      <td>14.4436</td>\n",
       "      <td>78.1264</td>\n",
       "      <td>102.167</td>\n",
       "      <td>92.5</td>\n",
       "      <td>444.118</td>\n",
       "      <td>-42.1927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PSSA3.SA</th>\n",
       "      <td>48.8467</td>\n",
       "      <td>-0.00129241</td>\n",
       "      <td>0.00254461</td>\n",
       "      <td>-1.6219e-05</td>\n",
       "      <td>79.6851</td>\n",
       "      <td>48.5597</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.300728</td>\n",
       "      <td>48.8459</td>\n",
       "      <td>46.7547</td>\n",
       "      <td>46.6933</td>\n",
       "      <td>47.04</td>\n",
       "      <td>8.68762</td>\n",
       "      <td>1.91954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PTBL3.SA</th>\n",
       "      <td>2.00809</td>\n",
       "      <td>0.0290886</td>\n",
       "      <td>0.0106846</td>\n",
       "      <td>-3.50571e-05</td>\n",
       "      <td>-829.75</td>\n",
       "      <td>53.0864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0628396</td>\n",
       "      <td>2.00802</td>\n",
       "      <td>9.06715</td>\n",
       "      <td>9.32985</td>\n",
       "      <td>8.61</td>\n",
       "      <td>280.973</td>\n",
       "      <td>-38.339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>QUAL3.SA</th>\n",
       "      <td>24.7011</td>\n",
       "      <td>0.042848</td>\n",
       "      <td>0.00398486</td>\n",
       "      <td>-2.06922e-05</td>\n",
       "      <td>-2070.73</td>\n",
       "      <td>50.6173</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0587638</td>\n",
       "      <td>24.7006</td>\n",
       "      <td>31.6372</td>\n",
       "      <td>33.0148</td>\n",
       "      <td>31.11</td>\n",
       "      <td>30.331</td>\n",
       "      <td>-10.3012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RADL3.SA</th>\n",
       "      <td>20.9835</td>\n",
       "      <td>0.0192649</td>\n",
       "      <td>0.00171285</td>\n",
       "      <td>-6.00364e-06</td>\n",
       "      <td>-3208.88</td>\n",
       "      <td>51.0288</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.57679</td>\n",
       "      <td>20.9833</td>\n",
       "      <td>25.1965</td>\n",
       "      <td>25.6855</td>\n",
       "      <td>24.85</td>\n",
       "      <td>19.759</td>\n",
       "      <td>-7.77999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RAIL3.SA</th>\n",
       "      <td>22.0863</td>\n",
       "      <td>-0.0119075</td>\n",
       "      <td>0.00131714</td>\n",
       "      <td>-8.37578e-06</td>\n",
       "      <td>1421.66</td>\n",
       "      <td>48.1481</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.67379</td>\n",
       "      <td>22.0862</td>\n",
       "      <td>20.0931</td>\n",
       "      <td>19.8559</td>\n",
       "      <td>19.75</td>\n",
       "      <td>-0.252525</td>\n",
       "      <td>5.91433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RANI3.SA</th>\n",
       "      <td>3.26598</td>\n",
       "      <td>0.0113765</td>\n",
       "      <td>0.00873315</td>\n",
       "      <td>-4.00964e-05</td>\n",
       "      <td>-283.729</td>\n",
       "      <td>53.9095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.63944</td>\n",
       "      <td>3.26585</td>\n",
       "      <td>5.62797</td>\n",
       "      <td>5.69203</td>\n",
       "      <td>5.6</td>\n",
       "      <td>104.38</td>\n",
       "      <td>-20.8406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RCSL4.SA</th>\n",
       "      <td>1.5446</td>\n",
       "      <td>-4.50595e-05</td>\n",
       "      <td>0.010044</td>\n",
       "      <td>-5.97059e-05</td>\n",
       "      <td>0.754692</td>\n",
       "      <td>55.144</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-9.38117</td>\n",
       "      <td>1.54451</td>\n",
       "      <td>1.38057</td>\n",
       "      <td>1.38043</td>\n",
       "      <td>1.4</td>\n",
       "      <td>48.9362</td>\n",
       "      <td>5.16097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SANB11.SA</th>\n",
       "      <td>22.9599</td>\n",
       "      <td>0.0798353</td>\n",
       "      <td>0.00129974</td>\n",
       "      <td>6.08967e-06</td>\n",
       "      <td>13110</td>\n",
       "      <td>49.3827</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.406209</td>\n",
       "      <td>22.96</td>\n",
       "      <td>38.2074</td>\n",
       "      <td>41.3816</td>\n",
       "      <td>40.94</td>\n",
       "      <td>48.4947</td>\n",
       "      <td>-21.9589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SEER3.SA</th>\n",
       "      <td>15.9612</td>\n",
       "      <td>-0.0113769</td>\n",
       "      <td>0.00171588</td>\n",
       "      <td>-1.96114e-05</td>\n",
       "      <td>580.118</td>\n",
       "      <td>47.7366</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-3.3969</td>\n",
       "      <td>15.9609</td>\n",
       "      <td>11.8404</td>\n",
       "      <td>11.7066</td>\n",
       "      <td>11.5</td>\n",
       "      <td>-27.8997</td>\n",
       "      <td>19.3952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SLCE3.SA</th>\n",
       "      <td>18.8718</td>\n",
       "      <td>0.071039</td>\n",
       "      <td>0.000563175</td>\n",
       "      <td>2.05736e-05</td>\n",
       "      <td>3452.92</td>\n",
       "      <td>53.0864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.949624</td>\n",
       "      <td>18.8722</td>\n",
       "      <td>39.8783</td>\n",
       "      <td>42.8287</td>\n",
       "      <td>42.47</td>\n",
       "      <td>99.4833</td>\n",
       "      <td>-27.7818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SMLS3.SA</th>\n",
       "      <td>9.51893</td>\n",
       "      <td>0.0563825</td>\n",
       "      <td>0.00535525</td>\n",
       "      <td>-6.91882e-06</td>\n",
       "      <td>-8149.14</td>\n",
       "      <td>53.0864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.734171</td>\n",
       "      <td>9.51886</td>\n",
       "      <td>22.9747</td>\n",
       "      <td>24.3283</td>\n",
       "      <td>24.8</td>\n",
       "      <td>145.545</td>\n",
       "      <td>-30.8087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SMTO3.SA</th>\n",
       "      <td>16.1315</td>\n",
       "      <td>0.0606347</td>\n",
       "      <td>0.00531298</td>\n",
       "      <td>-1.95889e-05</td>\n",
       "      <td>-3095.36</td>\n",
       "      <td>54.321</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.581394</td>\n",
       "      <td>16.1312</td>\n",
       "      <td>28.7484</td>\n",
       "      <td>30.5246</td>\n",
       "      <td>28.91</td>\n",
       "      <td>87.7273</td>\n",
       "      <td>-22.1011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SOMA3.SA</th>\n",
       "      <td>-1.26431</td>\n",
       "      <td>0.0754204</td>\n",
       "      <td>-0.000486269</td>\n",
       "      <td>1.38675e-05</td>\n",
       "      <td>5438.64</td>\n",
       "      <td>53.1646</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.467003</td>\n",
       "      <td>-1.26433</td>\n",
       "      <td>13.6023</td>\n",
       "      <td>14.6687</td>\n",
       "      <td>14</td>\n",
       "      <td>26.9266</td>\n",
       "      <td>-54.5155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STBP3.SA</th>\n",
       "      <td>4.29979</td>\n",
       "      <td>0.00651692</td>\n",
       "      <td>-0.00084013</td>\n",
       "      <td>2.2527e-05</td>\n",
       "      <td>289.294</td>\n",
       "      <td>53.4979</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-2.2489</td>\n",
       "      <td>4.29989</td>\n",
       "      <td>6.70547</td>\n",
       "      <td>6.74953</td>\n",
       "      <td>6.76</td>\n",
       "      <td>40.249</td>\n",
       "      <td>-18.1961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUZB3.SA</th>\n",
       "      <td>32.4322</td>\n",
       "      <td>0.147468</td>\n",
       "      <td>0.00349694</td>\n",
       "      <td>-2.49395e-07</td>\n",
       "      <td>-591305</td>\n",
       "      <td>51.8519</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.11032</td>\n",
       "      <td>32.4322</td>\n",
       "      <td>67.8674</td>\n",
       "      <td>78.5896</td>\n",
       "      <td>72.5</td>\n",
       "      <td>113.298</td>\n",
       "      <td>-27.633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TAEE11.SA</th>\n",
       "      <td>23.8361</td>\n",
       "      <td>0.0377951</td>\n",
       "      <td>0.00184219</td>\n",
       "      <td>1.04618e-06</td>\n",
       "      <td>36126.9</td>\n",
       "      <td>51.6529</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.821215</td>\n",
       "      <td>23.8361</td>\n",
       "      <td>34.9979</td>\n",
       "      <td>36.3568</td>\n",
       "      <td>36.1</td>\n",
       "      <td>58.8908</td>\n",
       "      <td>-16.986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TASA4.SA</th>\n",
       "      <td>0.810911</td>\n",
       "      <td>0.0773134</td>\n",
       "      <td>0.00627769</td>\n",
       "      <td>1.61243e-05</td>\n",
       "      <td>4794.85</td>\n",
       "      <td>52.6749</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.826044</td>\n",
       "      <td>0.810924</td>\n",
       "      <td>22.5082</td>\n",
       "      <td>24.2838</td>\n",
       "      <td>22.72</td>\n",
       "      <td>475.19</td>\n",
       "      <td>-48.2154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TIET11.SA</th>\n",
       "      <td>13.4831</td>\n",
       "      <td>0.0121555</td>\n",
       "      <td>0.00182636</td>\n",
       "      <td>-3.00075e-06</td>\n",
       "      <td>-4050.83</td>\n",
       "      <td>52.8926</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.664729</td>\n",
       "      <td>13.4831</td>\n",
       "      <td>17.0652</td>\n",
       "      <td>17.2748</td>\n",
       "      <td>17.44</td>\n",
       "      <td>36.1436</td>\n",
       "      <td>-11.3444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TOTS3.SA</th>\n",
       "      <td>27.1312</td>\n",
       "      <td>0.00388674</td>\n",
       "      <td>-0.00219468</td>\n",
       "      <td>1.89319e-05</td>\n",
       "      <td>205.301</td>\n",
       "      <td>55.9671</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.50057</td>\n",
       "      <td>27.1318</td>\n",
       "      <td>28.5289</td>\n",
       "      <td>28.6401</td>\n",
       "      <td>28.22</td>\n",
       "      <td>-39.377</td>\n",
       "      <td>-1.92814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TRPL4.SA</th>\n",
       "      <td>16.612</td>\n",
       "      <td>0.040085</td>\n",
       "      <td>0.00198483</td>\n",
       "      <td>-2.37833e-06</td>\n",
       "      <td>-16854.2</td>\n",
       "      <td>51.0288</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.189316</td>\n",
       "      <td>16.612</td>\n",
       "      <td>24.332</td>\n",
       "      <td>25.325</td>\n",
       "      <td>25.59</td>\n",
       "      <td>47.1535</td>\n",
       "      <td>-17.542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>USIM5.SA</th>\n",
       "      <td>3.81597</td>\n",
       "      <td>0.0537611</td>\n",
       "      <td>0.00797452</td>\n",
       "      <td>-1.80783e-05</td>\n",
       "      <td>-2973.8</td>\n",
       "      <td>51.8519</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.5341</td>\n",
       "      <td>3.8159</td>\n",
       "      <td>16.5251</td>\n",
       "      <td>17.4199</td>\n",
       "      <td>16.58</td>\n",
       "      <td>249.789</td>\n",
       "      <td>-38.4925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VALE3.SA</th>\n",
       "      <td>34.8578</td>\n",
       "      <td>0.239648</td>\n",
       "      <td>0.00454144</td>\n",
       "      <td>-4.62031e-06</td>\n",
       "      <td>-51868.3</td>\n",
       "      <td>52.2634</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.13003</td>\n",
       "      <td>34.8577</td>\n",
       "      <td>82.7642</td>\n",
       "      <td>105.07</td>\n",
       "      <td>95.53</td>\n",
       "      <td>148.971</td>\n",
       "      <td>-31.7556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VVAR3.SA</th>\n",
       "      <td>13.0355</td>\n",
       "      <td>0.0169714</td>\n",
       "      <td>0.0190955</td>\n",
       "      <td>-0.000123164</td>\n",
       "      <td>-137.795</td>\n",
       "      <td>51.8519</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0171571</td>\n",
       "      <td>13.0339</td>\n",
       "      <td>11.854</td>\n",
       "      <td>12.055</td>\n",
       "      <td>11.96</td>\n",
       "      <td>119.45</td>\n",
       "      <td>4.48947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WEGE3.SA</th>\n",
       "      <td>39.7185</td>\n",
       "      <td>0.201737</td>\n",
       "      <td>0.00913</td>\n",
       "      <td>-4.60014e-05</td>\n",
       "      <td>-4385.44</td>\n",
       "      <td>54.7325</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.804734</td>\n",
       "      <td>39.7167</td>\n",
       "      <td>64.5661</td>\n",
       "      <td>78.9809</td>\n",
       "      <td>72.97</td>\n",
       "      <td>116.336</td>\n",
       "      <td>-22.7856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YDUQ3.SA</th>\n",
       "      <td>29.535</td>\n",
       "      <td>0.00589346</td>\n",
       "      <td>0.00443656</td>\n",
       "      <td>-2.98929e-05</td>\n",
       "      <td>-197.152</td>\n",
       "      <td>46.9136</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.638261</td>\n",
       "      <td>29.5341</td>\n",
       "      <td>27.3076</td>\n",
       "      <td>27.4674</td>\n",
       "      <td>27.09</td>\n",
       "      <td>3.12143</td>\n",
       "      <td>4.5111</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Reg_price   Coef_price      Reg_int     Coef_int Rel_price_ret  \\\n",
       "ABEV3.SA    12.0936    0.0134759   0.00110923 -3.33518e-07      -40405.2   \n",
       "AERI3.SA   -3.25147    0.0545038  0.000277664  1.33361e-05       4086.95   \n",
       "ALPA4.SA    26.5389    0.0645494   0.00536622 -2.72935e-05      -2365.01   \n",
       "ANIM3.SA    25.4991  0.000280565    0.0086771 -7.94031e-05      -3.53343   \n",
       "AZUL4.SA    12.5214      0.12242   0.00452644 -4.19975e-06      -29149.4   \n",
       "BEEF3.SA    12.6667   -0.0127695    0.0075359 -5.05503e-05        252.61   \n",
       "BIDI4.SA    3.33513      0.17122   0.00454223  2.17822e-05       7860.55   \n",
       "BKBR3.SA    10.7676  -0.00250519   0.00375005 -2.54677e-05       98.3671   \n",
       "BMGB4.SA    4.65172   0.00232217   0.00522117 -2.79742e-05      -83.0111   \n",
       "BPAN4.SA   -24.7194     0.470072     -2.45786     0.036099       13.0218   \n",
       "BRAP4.SA    25.1743     0.179678   0.00554649 -1.40092e-05      -12825.7   \n",
       "BRFS3.SA    19.5264    0.0103121   0.00526307 -2.22366e-05      -463.747   \n",
       "BRKM5.SA    20.5091    0.0315566   0.00275021  8.25936e-06       3820.71   \n",
       "BTOW3.SA    97.2179   -0.0751727     0.013038 -9.53383e-05       788.484   \n",
       "CAML3.SA    10.0324   0.00816934   0.00641996  -4.1261e-05      -197.992   \n",
       "CASH3.SA   -7.91209     0.126662  -0.00154386  4.82234e-05       2626.57   \n",
       "CEAB3.SA    9.43923    0.0142248   0.00921757 -5.37877e-05      -264.462   \n",
       "CIEL3.SA    4.64331  -0.00444485 -6.18874e-05 -2.07368e-06       2143.46   \n",
       "CNTO3.SA    30.2215   -0.0223778   0.00234068 -1.24743e-05        1793.9   \n",
       "COGN3.SA    6.48579  -0.00881663   0.00497961 -4.29593e-05       205.232   \n",
       "CPFE3.SA    27.6049    0.0149983    0.0034692 -1.88413e-05      -796.034   \n",
       "CPLE3.SA    64.5424   -0.0651866   0.00621486 -7.36987e-05       884.502   \n",
       "CPLE6.SA    66.1425   -0.0574806   0.00856916  -8.7937e-05       653.656   \n",
       "CRFB3.SA    19.7282 -0.000611192  -0.00199708  1.96037e-05      -31.1774   \n",
       "CSAN3.SA    61.7635     0.100612   0.00361612 -9.43501e-06      -10663.7   \n",
       "CSNA3.SA    3.14434     0.134283    0.0095891  -1.8766e-05      -7155.66   \n",
       "DMMO3.SA    1.37671  -0.00127478    0.0182128 -0.000120472       10.5816   \n",
       "DTEX3.SA    10.0165    0.0465516   0.00691186 -2.97199e-05      -1566.35   \n",
       "ELET3.SA    25.3208    0.0370729   0.00622918 -2.87828e-05      -1288.02   \n",
       "ELET6.SA     27.266    0.0286109   0.00469919 -2.10338e-05      -1360.23   \n",
       "...             ...          ...          ...          ...           ...   \n",
       "PETR3.SA    18.4363    0.0349484    0.0090858 -5.06246e-05      -690.344   \n",
       "PETR4.SA    18.0419    0.0356863   0.00804615 -4.31261e-05      -827.487   \n",
       "PETZ3.SA   -4.87948     0.119973  0.000533084  4.50915e-06       26606.6   \n",
       "POSI3.SA    4.29925   0.00316406   0.00497556 -1.76613e-05      -179.152   \n",
       "PRIO3.SA    14.4439     0.268627    0.0106452 -2.08272e-05      -12897.9   \n",
       "PSSA3.SA    48.8467  -0.00129241   0.00254461  -1.6219e-05       79.6851   \n",
       "PTBL3.SA    2.00809    0.0290886    0.0106846 -3.50571e-05       -829.75   \n",
       "QUAL3.SA    24.7011     0.042848   0.00398486 -2.06922e-05      -2070.73   \n",
       "RADL3.SA    20.9835    0.0192649   0.00171285 -6.00364e-06      -3208.88   \n",
       "RAIL3.SA    22.0863   -0.0119075   0.00131714 -8.37578e-06       1421.66   \n",
       "RANI3.SA    3.26598    0.0113765   0.00873315 -4.00964e-05      -283.729   \n",
       "RCSL4.SA     1.5446 -4.50595e-05     0.010044 -5.97059e-05      0.754692   \n",
       "SANB11.SA   22.9599    0.0798353   0.00129974  6.08967e-06         13110   \n",
       "SEER3.SA    15.9612   -0.0113769   0.00171588 -1.96114e-05       580.118   \n",
       "SLCE3.SA    18.8718     0.071039  0.000563175  2.05736e-05       3452.92   \n",
       "SMLS3.SA    9.51893    0.0563825   0.00535525 -6.91882e-06      -8149.14   \n",
       "SMTO3.SA    16.1315    0.0606347   0.00531298 -1.95889e-05      -3095.36   \n",
       "SOMA3.SA   -1.26431    0.0754204 -0.000486269  1.38675e-05       5438.64   \n",
       "STBP3.SA    4.29979   0.00651692  -0.00084013   2.2527e-05       289.294   \n",
       "SUZB3.SA    32.4322     0.147468   0.00349694 -2.49395e-07       -591305   \n",
       "TAEE11.SA   23.8361    0.0377951   0.00184219  1.04618e-06       36126.9   \n",
       "TASA4.SA   0.810911    0.0773134   0.00627769  1.61243e-05       4794.85   \n",
       "TIET11.SA   13.4831    0.0121555   0.00182636 -3.00075e-06      -4050.83   \n",
       "TOTS3.SA    27.1312   0.00388674  -0.00219468  1.89319e-05       205.301   \n",
       "TRPL4.SA     16.612     0.040085   0.00198483 -2.37833e-06      -16854.2   \n",
       "USIM5.SA    3.81597    0.0537611   0.00797452 -1.80783e-05       -2973.8   \n",
       "VALE3.SA    34.8578     0.239648   0.00454144 -4.62031e-06      -51868.3   \n",
       "VVAR3.SA    13.0355    0.0169714    0.0190955 -0.000123164      -137.795   \n",
       "WEGE3.SA    39.7185     0.201737      0.00913 -4.60014e-05      -4385.44   \n",
       "YDUQ3.SA     29.535   0.00589346   0.00443656 -2.98929e-05      -197.152   \n",
       "\n",
       "          Pct_up_day Pct_up_month      Sharpe Base_price Target_buy  \\\n",
       "ABEV3.SA     51.8519          NaN    -1.20764    12.0936    15.0657   \n",
       "AERI3.SA     48.8372          NaN    0.361511   -3.25151    9.00168   \n",
       "ALPA4.SA     52.6749          NaN    0.392118    26.5382    34.7423   \n",
       "ANIM3.SA     50.2058          NaN   -0.924437    25.4971    8.94107   \n",
       "AZUL4.SA     51.0288          NaN    0.507608    12.5214    36.1776   \n",
       "BEEF3.SA     47.3251          NaN    -1.13087     12.666    9.93421   \n",
       "BIDI4.SA     57.0248          NaN     1.00022    3.33521    47.3659   \n",
       "BKBR3.SA     50.8264          NaN    -2.51257    10.7673    9.34298   \n",
       "BMGB4.SA     49.5868          NaN    -4.51686    4.65159    5.13533   \n",
       "BPAN4.SA     49.3827          NaN -0.00222517   -25.6118    8.23559   \n",
       "BRAP4.SA     52.6749          NaN    0.929584    25.1739    57.1956   \n",
       "BRFS3.SA     46.0905          NaN     0.65336    19.5259    24.4675   \n",
       "BRKM5.SA     50.2058          NaN     1.35737    20.5093    36.5271   \n",
       "BTOW3.SA     43.6214          NaN   0.0380775    97.2086    64.1091   \n",
       "CAML3.SA     51.8519          NaN     -1.1165     10.032    10.4959   \n",
       "CASH3.SA     57.3034          NaN     1.57223   -7.91247    22.2675   \n",
       "CEAB3.SA     48.7603          NaN   -0.628457    9.43872    11.0605   \n",
       "CIEL3.SA      45.679          NaN    -5.58283     4.6433    3.62859   \n",
       "CNTO3.SA     42.3868          NaN   -0.767965    30.2211    26.2378   \n",
       "COGN3.SA      44.856          NaN    -2.41357    6.48551    3.99247   \n",
       "CPFE3.SA     53.0864          NaN  -0.0845844    27.6043     30.392   \n",
       "CPLE3.SA     50.2058          NaN    -1.60046    64.5376    6.94262   \n",
       "CPLE6.SA     50.2058          NaN    -1.35899    66.1367    7.15613   \n",
       "CRFB3.SA     50.2058          NaN    -2.43295    19.7285    20.4577   \n",
       "CSAN3.SA     48.5597          NaN     1.16279    61.7629    87.2616   \n",
       "CSNA3.SA     53.4979          NaN    0.875142    3.14428     32.427   \n",
       "DMMO3.SA     46.0905          NaN    -10.9499    1.37654   0.883112   \n",
       "DTEX3.SA     50.2058          NaN    0.268506    10.0162    18.7528   \n",
       "ELET3.SA     48.1481          NaN    0.628326      25.32    32.5352   \n",
       "ELET6.SA     49.3827          NaN    0.514253    27.2654    33.3444   \n",
       "...              ...          ...         ...        ...        ...   \n",
       "PETR3.SA     53.4979          NaN    0.388007    18.4353    22.5714   \n",
       "PETR4.SA     53.0864          NaN    0.372988    18.0411    22.8639   \n",
       "PETZ3.SA     51.5873          NaN    0.111353   -4.87951    18.8067   \n",
       "POSI3.SA     49.7942          NaN    -2.65723    4.29917    5.94942   \n",
       "PRIO3.SA     48.1481          NaN     1.29755    14.4436    78.1264   \n",
       "PSSA3.SA     48.5597          NaN   -0.300728    48.8459    46.7547   \n",
       "PTBL3.SA     53.0864          NaN  -0.0628396    2.00802    9.06715   \n",
       "QUAL3.SA     50.6173          NaN   0.0587638    24.7006    31.6372   \n",
       "RADL3.SA     51.0288          NaN    -0.57679    20.9833    25.1965   \n",
       "RAIL3.SA     48.1481          NaN    -1.67379    22.0862    20.0931   \n",
       "RANI3.SA     53.9095          NaN    -1.63944    3.26585    5.62797   \n",
       "RCSL4.SA      55.144          NaN    -9.38117    1.54451    1.38057   \n",
       "SANB11.SA    49.3827          NaN    0.406209      22.96    38.2074   \n",
       "SEER3.SA     47.7366          NaN     -3.3969    15.9609    11.8404   \n",
       "SLCE3.SA     53.0864          NaN    0.949624    18.8722    39.8783   \n",
       "SMLS3.SA     53.0864          NaN    0.734171    9.51886    22.9747   \n",
       "SMTO3.SA      54.321          NaN    0.581394    16.1312    28.7484   \n",
       "SOMA3.SA     53.1646          NaN   -0.467003   -1.26433    13.6023   \n",
       "STBP3.SA     53.4979          NaN     -2.2489    4.29989    6.70547   \n",
       "SUZB3.SA     51.8519          NaN     1.11032    32.4322    67.8674   \n",
       "TAEE11.SA    51.6529          NaN    0.821215    23.8361    34.9979   \n",
       "TASA4.SA     52.6749          NaN    0.826044   0.810924    22.5082   \n",
       "TIET11.SA    52.8926          NaN   -0.664729    13.4831    17.0652   \n",
       "TOTS3.SA     55.9671          NaN    -1.50057    27.1318    28.5289   \n",
       "TRPL4.SA     51.0288          NaN    0.189316     16.612     24.332   \n",
       "USIM5.SA     51.8519          NaN      0.5341     3.8159    16.5251   \n",
       "VALE3.SA     52.2634          NaN     1.13003    34.8577    82.7642   \n",
       "VVAR3.SA     51.8519          NaN  -0.0171571    13.0339     11.854   \n",
       "WEGE3.SA     54.7325          NaN    0.804734    39.7167    64.5661   \n",
       "YDUQ3.SA     46.9136          NaN   -0.638261    29.5341    27.3076   \n",
       "\n",
       "          Target_sell Actual_price  Ret_real Stop_loss  \n",
       "ABEV3.SA      15.2693        15.15    21.297  -10.0871  \n",
       "AERI3.SA      9.49943          9.1   49.1803  -67.8654  \n",
       "ALPA4.SA      37.0637        36.69   50.6158  -13.8345  \n",
       "ANIM3.SA      8.94293         9.13  -56.2739   89.6334  \n",
       "AZUL4.SA      40.7654        37.47   96.2808  -33.2915  \n",
       "BEEF3.SA      9.80679         9.83   29.0026   14.4253  \n",
       "BIDI4.SA      56.3313        50.98   373.792  -46.7289  \n",
       "BKBR3.SA      9.31924         9.48 -0.732984   6.78965  \n",
       "BMGB4.SA      5.14717         5.15   41.0959  -4.83898  \n",
       "BPAN4.SA      13.7464        10.78     115.6  -168.793  \n",
       "BRAP4.SA      68.4134        65.37   138.577   -30.745  \n",
       "BRFS3.SA      24.7195        24.39    68.091  -9.97144  \n",
       "BRKM5.SA      37.7049        37.83   113.729  -22.8928  \n",
       "BTOW3.SA      59.5009        59.36    16.415   31.8806  \n",
       "CAML3.SA      10.5811        10.29   32.2622   -1.2535  \n",
       "CASH3.SA      25.2234        23.02   142.571  -67.1861  \n",
       "CEAB3.SA      11.2197           11   54.9296  -7.09674  \n",
       "CIEL3.SA      3.61241         3.63  -22.5071   13.9572  \n",
       "CNTO3.SA      25.6432        26.69   2.02599    6.6151  \n",
       "COGN3.SA      3.95753         3.84  -24.1107   34.4468  \n",
       "CPFE3.SA        30.85        30.27    26.125  -4.40314  \n",
       "CPLE3.SA      6.50238         6.71  -88.3689   430.906  \n",
       "CPLE6.SA      6.75487         6.98  -86.6027   423.758  \n",
       "CRFB3.SA      20.4453        22.22   4.31925  -5.60634  \n",
       "CSAN3.SA      96.4824         90.8   66.8504  -15.9896  \n",
       "CSNA3.SA       37.003        35.14    398.44  -45.5261  \n",
       "DMMO3.SA     0.881888         0.87   35.9375   29.1115  \n",
       "DTEX3.SA      19.6432        18.76   95.0104  -23.3042  \n",
       "ELET3.SA      33.7608        33.77   69.2732   -12.511  \n",
       "ELET6.SA      34.3106        34.26    51.929  -10.2081  \n",
       "...               ...          ...       ...       ...  \n",
       "PETR3.SA      23.3696        23.25   79.6754  -10.3541  \n",
       "PETR4.SA      23.6891        23.42   75.0374  -11.4835  \n",
       "PETZ3.SA      21.1958        19.29    24.693  -62.6478  \n",
       "POSI3.SA      5.96858         5.55   59.9424  -11.2687  \n",
       "PRIO3.SA      102.167         92.5   444.118  -42.1927  \n",
       "PSSA3.SA      46.6933        47.04   8.68762   1.91954  \n",
       "PTBL3.SA      9.32985         8.61   280.973   -38.339  \n",
       "QUAL3.SA      33.0148        31.11    30.331  -10.3012  \n",
       "RADL3.SA      25.6855        24.85    19.759  -7.77999  \n",
       "RAIL3.SA      19.8559        19.75 -0.252525   5.91433  \n",
       "RANI3.SA      5.69203          5.6    104.38  -20.8406  \n",
       "RCSL4.SA      1.38043          1.4   48.9362   5.16097  \n",
       "SANB11.SA     41.3816        40.94   48.4947  -21.9589  \n",
       "SEER3.SA      11.7066         11.5  -27.8997   19.3952  \n",
       "SLCE3.SA      42.8287        42.47   99.4833  -27.7818  \n",
       "SMLS3.SA      24.3283         24.8   145.545  -30.8087  \n",
       "SMTO3.SA      30.5246        28.91   87.7273  -22.1011  \n",
       "SOMA3.SA      14.6687           14   26.9266  -54.5155  \n",
       "STBP3.SA      6.74953         6.76    40.249  -18.1961  \n",
       "SUZB3.SA      78.5896         72.5   113.298   -27.633  \n",
       "TAEE11.SA     36.3568         36.1   58.8908   -16.986  \n",
       "TASA4.SA      24.2838        22.72    475.19  -48.2154  \n",
       "TIET11.SA     17.2748        17.44   36.1436  -11.3444  \n",
       "TOTS3.SA      28.6401        28.22   -39.377  -1.92814  \n",
       "TRPL4.SA       25.325        25.59   47.1535   -17.542  \n",
       "USIM5.SA      17.4199        16.58   249.789  -38.4925  \n",
       "VALE3.SA       105.07        95.53   148.971  -31.7556  \n",
       "VVAR3.SA       12.055        11.96    119.45   4.48947  \n",
       "WEGE3.SA      78.9809        72.97   116.336  -22.7856  \n",
       "YDUQ3.SA      27.4674        27.09   3.12143    4.5111  \n",
       "\n",
       "[100 rows x 14 columns]"
      ]
     },
     "execution_count": 380,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "finals_stocks"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Retorno dos ativos</h2>    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 381,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ETER3.SA      556.028\n",
       "TASA4.SA       475.19\n",
       "PRIO3.SA      444.118\n",
       "LWSA3.SA      405.495\n",
       "CSNA3.SA       398.44\n",
       "BIDI4.SA      373.792\n",
       "PTBL3.SA      280.973\n",
       "USIM5.SA      249.789\n",
       "OIBR3.SA      246.154\n",
       "GGBR4.SA      197.297\n",
       "GOAU4.SA      189.545\n",
       "VALE3.SA      148.971\n",
       "OIBR4.SA      145.833\n",
       "SMLS3.SA      145.545\n",
       "CASH3.SA      142.571\n",
       "BRAP4.SA      138.577\n",
       "VVAR3.SA       119.45\n",
       "WEGE3.SA      116.336\n",
       "BPAN4.SA        115.6\n",
       "BRKM5.SA      113.729\n",
       "SUZB3.SA      113.298\n",
       "RANI3.SA       104.38\n",
       "SLCE3.SA      99.4833\n",
       "ENAT3.SA      98.4615\n",
       "MGLU3.SA       97.332\n",
       "AZUL4.SA      96.2808\n",
       "DTEX3.SA      95.0104\n",
       "LINX3.SA      94.9432\n",
       "ENEV3.SA      90.9302\n",
       "MRFG3.SA      88.1564\n",
       "               ...   \n",
       "ENGI11.SA      16.904\n",
       "BTOW3.SA       16.415\n",
       "LAME4.SA      14.4597\n",
       "GFSA3.SA      9.64706\n",
       "PSSA3.SA      8.68762\n",
       "HYPE3.SA      8.61196\n",
       "MYPK3.SA      7.83242\n",
       "MEAL3.SA       6.3253\n",
       "ENJU3.SA      5.02049\n",
       "GRND3.SA      4.69799\n",
       "CRFB3.SA      4.31925\n",
       "YDUQ3.SA      3.12143\n",
       "CNTO3.SA      2.02599\n",
       "NEOE3.SA     0.119832\n",
       "RAIL3.SA    -0.252525\n",
       "BKBR3.SA    -0.732984\n",
       "ODPV3.SA     -0.81663\n",
       "MDIA3.SA     -1.16429\n",
       "LAVV3.SA     -13.0926\n",
       "GMAT3.SA      -13.311\n",
       "HBSA3.SA     -19.9461\n",
       "CIEL3.SA     -22.5071\n",
       "COGN3.SA     -24.1107\n",
       "SEER3.SA     -27.8997\n",
       "TOTS3.SA      -39.377\n",
       "IRBR3.SA     -40.6615\n",
       "PCAR3.SA     -51.4201\n",
       "ANIM3.SA     -56.2739\n",
       "CPLE6.SA     -86.6027\n",
       "CPLE3.SA     -88.3689\n",
       "Name: Ret_real, Length: 100, dtype: object"
      ]
     },
     "execution_count": 381,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "finals_stocks[\"Ret_real\"].sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Relacao entre coeficientes lineares</h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 382,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LAVV3.SA      150326\n",
       "TAEE11.SA    36126.9\n",
       "PETZ3.SA     26606.6\n",
       "SANB11.SA      13110\n",
       "BIDI4.SA     7860.55\n",
       "IRBR3.SA     5717.94\n",
       "SOMA3.SA     5438.64\n",
       "TASA4.SA     4794.85\n",
       "AERI3.SA     4086.95\n",
       "BRKM5.SA     3820.71\n",
       "SLCE3.SA     3452.92\n",
       "ETER3.SA     3411.61\n",
       "CASH3.SA     2626.57\n",
       "ODPV3.SA     2487.53\n",
       "CIEL3.SA     2143.46\n",
       "CNTO3.SA      1793.9\n",
       "RAIL3.SA     1421.66\n",
       "NGRD3.SA     1289.42\n",
       "JBSS3.SA     1280.64\n",
       "MDIA3.SA     939.851\n",
       "CPLE3.SA     884.502\n",
       "BTOW3.SA     788.484\n",
       "CPLE6.SA     653.656\n",
       "SEER3.SA     580.118\n",
       "LAME4.SA     387.947\n",
       "LAME3.SA     357.216\n",
       "NEOE3.SA     308.948\n",
       "STBP3.SA     289.294\n",
       "BEEF3.SA      252.61\n",
       "EMBR3.SA     240.477\n",
       "              ...   \n",
       "LWSA3.SA    -1753.63\n",
       "NTCO3.SA    -1793.99\n",
       "QUAL3.SA    -2070.73\n",
       "KLBN11.SA   -2197.81\n",
       "HYPE3.SA    -2359.56\n",
       "ALPA4.SA    -2365.01\n",
       "GGBR4.SA    -2597.63\n",
       "LINX3.SA    -2814.96\n",
       "USIM5.SA     -2973.8\n",
       "SMTO3.SA    -3095.36\n",
       "ENEV3.SA    -3184.41\n",
       "RADL3.SA    -3208.88\n",
       "TIET11.SA   -4050.83\n",
       "WEGE3.SA    -4385.44\n",
       "HBSA3.SA    -4913.23\n",
       "CSNA3.SA    -7155.66\n",
       "ENAT3.SA    -7441.24\n",
       "GNDI3.SA    -7521.44\n",
       "SMLS3.SA    -8149.14\n",
       "GMAT3.SA    -10557.6\n",
       "CSAN3.SA    -10663.7\n",
       "ENJU3.SA    -11242.9\n",
       "BRAP4.SA    -12825.7\n",
       "PRIO3.SA    -12897.9\n",
       "TRPL4.SA    -16854.2\n",
       "AZUL4.SA    -29149.4\n",
       "LJQQ3.SA    -36794.5\n",
       "ABEV3.SA    -40405.2\n",
       "VALE3.SA    -51868.3\n",
       "SUZB3.SA     -591305\n",
       "Name: Rel_price_ret, Length: 100, dtype: object"
      ]
     },
     "execution_count": 382,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "finals_stocks[\"Rel_price_ret\"].sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Pivoteamento de preços e retornos</h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 383,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ETER3.SA',\n",
       " 'TASA4.SA',\n",
       " 'BIDI4.SA',\n",
       " 'CSNA3.SA',\n",
       " 'PRIO3.SA',\n",
       " 'USIM5.SA',\n",
       " 'SMLS3.SA',\n",
       " 'BRAP4.SA',\n",
       " 'SUZB3.SA',\n",
       " 'BRKM5.SA',\n",
       " 'ENAT3.SA',\n",
       " 'PTBL3.SA',\n",
       " 'AZUL4.SA',\n",
       " 'VALE3.SA',\n",
       " 'GGBR4.SA',\n",
       " 'GOAU4.SA',\n",
       " 'SLCE3.SA',\n",
       " 'TAEE11.SA',\n",
       " 'RANI3.SA',\n",
       " 'LWSA3.SA',\n",
       " 'SMTO3.SA',\n",
       " 'GNDI3.SA',\n",
       " 'SANB11.SA',\n",
       " 'ENEV3.SA',\n",
       " 'POSI3.SA',\n",
       " 'TRPL4.SA',\n",
       " 'GOLL4.SA',\n",
       " 'OIBR4.SA',\n",
       " 'CSAN3.SA',\n",
       " 'WEGE3.SA',\n",
       " 'OIBR3.SA',\n",
       " 'STBP3.SA',\n",
       " 'CASH3.SA',\n",
       " 'NGRD3.SA',\n",
       " 'AERI3.SA',\n",
       " 'MGLU3.SA',\n",
       " 'PCAR3.SA',\n",
       " 'CEAB3.SA',\n",
       " 'MRFG3.SA',\n",
       " 'HAPV3.SA',\n",
       " 'VVAR3.SA',\n",
       " 'DMMO3.SA',\n",
       " 'BPAN4.SA',\n",
       " 'DTEX3.SA',\n",
       " 'PETR3.SA',\n",
       " 'PETZ3.SA',\n",
       " 'TIET11.SA',\n",
       " 'ABEV3.SA',\n",
       " 'RCSL4.SA',\n",
       " 'LINX3.SA']"
      ]
     },
     "execution_count": 383,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ranking = pd.DataFrame()\n",
    "ranking['pos'] = range(1,len(finals_stocks)+1)\n",
    "ranking['Coef_int'] = finals_stocks['Coef_int'].sort_values(ascending = False).index\n",
    "ranking['Reg_int'] = finals_stocks['Reg_int'].sort_values(ascending = False).index\n",
    "a = ranking.pivot_table(columns='Coef_int', values='pos')\n",
    "b = ranking.pivot_table(columns='Reg_int', values='pos')\n",
    "t = pd.concat([a,b])\n",
    "rank = t.dropna(axis=1).sum()\n",
    "return_list = list(rank.sort_values(ascending = True).index[:50])\n",
    "best_names = return_list\n",
    "return_list"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Pivoteamento de correlacao, preços e retornos</h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 395,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['TASA4.SA',\n",
       " 'SUZB3.SA',\n",
       " 'BRAP4.SA',\n",
       " 'ETER3.SA',\n",
       " 'SLCE3.SA',\n",
       " 'VALE3.SA',\n",
       " 'RANI3.SA',\n",
       " 'PRIO3.SA',\n",
       " 'BIDI4.SA',\n",
       " 'CSNA3.SA',\n",
       " 'ENAT3.SA',\n",
       " 'LWSA3.SA',\n",
       " 'PCAR3.SA',\n",
       " 'MRFG3.SA',\n",
       " 'BPAN4.SA',\n",
       " 'NGRD3.SA',\n",
       " 'OIBR4.SA',\n",
       " 'BRKM5.SA',\n",
       " 'AERI3.SA',\n",
       " 'CASH3.SA',\n",
       " 'USIM5.SA',\n",
       " 'SMTO3.SA',\n",
       " 'DMMO3.SA',\n",
       " 'PETZ3.SA',\n",
       " 'TAEE11.SA']"
      ]
     },
     "execution_count": 395,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ranking = pd.DataFrame()\n",
    "ranking['pos'] = range(1,len(return_list)+1)\n",
    "ranking['Coefs'] = return_list\n",
    "ranking['Corre'] = best_corr[:50]\n",
    "ranking\n",
    "a = ranking.pivot_table(columns='Coefs', values='pos')\n",
    "b = ranking.pivot_table(columns='Corre', values='pos')\n",
    "t = pd.concat([a,b])\n",
    "rank = t.dropna(axis=1).sum()\n",
    "best_names = list(rank.sort_values(ascending = True).index[:25])\n",
    "best_names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Ativos propensos a um repique de alta</h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 385,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['AERI3.SA',\n",
       " 'BEEF3.SA',\n",
       " 'BMGB4.SA',\n",
       " 'BPAN4.SA',\n",
       " 'BRFS3.SA',\n",
       " 'BTOW3.SA',\n",
       " 'CEAB3.SA',\n",
       " 'CNTO3.SA',\n",
       " 'CSAN3.SA',\n",
       " 'DMMO3.SA',\n",
       " 'ELET3.SA',\n",
       " 'ELET6.SA',\n",
       " 'FLRY3.SA',\n",
       " 'GFSA3.SA',\n",
       " 'GOLL4.SA',\n",
       " 'GRND3.SA',\n",
       " 'JBSS3.SA',\n",
       " 'MEAL3.SA',\n",
       " 'MYPK3.SA',\n",
       " 'NEOE3.SA',\n",
       " 'NTCO3.SA',\n",
       " 'OIBR4.SA',\n",
       " 'POSI3.SA',\n",
       " 'PRIO3.SA',\n",
       " 'PSSA3.SA',\n",
       " 'SANB11.SA',\n",
       " 'YDUQ3.SA']"
      ]
     },
     "execution_count": 385,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    # Apenas ativos com retorno positivo e dias negativos\n",
    "\n",
    "finals_stocks\n",
    "select = finals_stocks.copy()\n",
    "select_2 = select.copy()\n",
    "\n",
    "list_append = []\n",
    "for i in range(len(select_2)):\n",
    "        if  select_2.iloc[i]['Pct_up_day'] < 50:\n",
    "            if select_2.iloc[i]['Ret_real'] > 0:\n",
    "                list_append.append(select_2.index[i])\n",
    "\n",
    "                \n",
    "best_names = list_append\n",
    "possible_raise = best_names\n",
    "best_names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Ativos propensos a um repique de baixa</h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 386,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ANIM3.SA',\n",
       " 'BKBR3.SA',\n",
       " 'CPLE3.SA',\n",
       " 'CPLE6.SA',\n",
       " 'GMAT3.SA',\n",
       " 'HBSA3.SA',\n",
       " 'LAVV3.SA',\n",
       " 'ODPV3.SA',\n",
       " 'PCAR3.SA',\n",
       " 'TOTS3.SA']"
      ]
     },
     "execution_count": 386,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    # Apenas ativos com retorno positivo e dias negativos\n",
    "\n",
    "finals_stocks\n",
    "select = finals_stocks.copy()\n",
    "select_2 = select.copy()\n",
    "\n",
    "list_append = []\n",
    "for i in range(len(select_2)):\n",
    "        if  select_2.iloc[i]['Pct_up_day'] > 50:\n",
    "            if select_2.iloc[i]['Ret_real'] < 0:\n",
    "                list_append.append(select_2.index[i])\n",
    "\n",
    "                \n",
    "best_names = list_append\n",
    "possible_raise_low = best_names\n",
    "best_names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Ativos quantificados em tendência de alta</h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 387,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ABEV3.SA',\n",
       " 'AERI3.SA',\n",
       " 'ALPA4.SA',\n",
       " 'AZUL4.SA',\n",
       " 'BIDI4.SA',\n",
       " 'BPAN4.SA',\n",
       " 'BRAP4.SA',\n",
       " 'CASH3.SA',\n",
       " 'CSAN3.SA',\n",
       " 'CSNA3.SA',\n",
       " 'DTEX3.SA',\n",
       " 'ELET6.SA',\n",
       " 'ENAT3.SA',\n",
       " 'ENEV3.SA',\n",
       " 'ETER3.SA',\n",
       " 'FLRY3.SA',\n",
       " 'GGBR4.SA',\n",
       " 'GNDI3.SA',\n",
       " 'HAPV3.SA',\n",
       " 'HYPE3.SA',\n",
       " 'KLBN11.SA',\n",
       " 'LAVV3.SA',\n",
       " 'LINX3.SA',\n",
       " 'LJQQ3.SA',\n",
       " 'LWSA3.SA',\n",
       " 'NGRD3.SA',\n",
       " 'NTCO3.SA',\n",
       " 'PETR3.SA',\n",
       " 'PETR4.SA',\n",
       " 'PETZ3.SA',\n",
       " 'PRIO3.SA',\n",
       " 'SANB11.SA',\n",
       " 'SLCE3.SA',\n",
       " 'SMTO3.SA',\n",
       " 'SOMA3.SA',\n",
       " 'SUZB3.SA',\n",
       " 'TAEE11.SA',\n",
       " 'TASA4.SA',\n",
       " 'USIM5.SA',\n",
       " 'VALE3.SA',\n",
       " 'VVAR3.SA',\n",
       " 'WEGE3.SA']"
      ]
     },
     "execution_count": 387,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    # Apenas ativos com preço equilibrado\n",
    "\n",
    "finals_stocks\n",
    "select = finals_stocks.copy()\n",
    "select_2 = select.copy()\n",
    "\n",
    "list_append = []\n",
    "for i in range(len(select_2)):\n",
    "        if  select_2.iloc[i]['Actual_price'] < select_2.iloc[i]['Target_sell']:\n",
    "            if select_2.iloc[i]['Actual_price'] > select_2.iloc[i]['Target_buy']:\n",
    "                list_append.append(select_2.index[i])\n",
    "\n",
    "                \n",
    "best_names = list_append\n",
    "balanced_prices = best_names\n",
    "best_names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Ativos com Sharpe > 0 </h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 388,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['AERI3.SA',\n",
       " 'ALPA4.SA',\n",
       " 'AZUL4.SA',\n",
       " 'BIDI4.SA',\n",
       " 'BRAP4.SA',\n",
       " 'BRFS3.SA',\n",
       " 'BRKM5.SA',\n",
       " 'BTOW3.SA',\n",
       " 'CASH3.SA',\n",
       " 'CSAN3.SA',\n",
       " 'CSNA3.SA',\n",
       " 'DTEX3.SA',\n",
       " 'ELET3.SA',\n",
       " 'ELET6.SA',\n",
       " 'ENAT3.SA',\n",
       " 'ENEV3.SA',\n",
       " 'ETER3.SA',\n",
       " 'GGBR4.SA',\n",
       " 'GNDI3.SA',\n",
       " 'GOAU4.SA',\n",
       " 'GOLL4.SA',\n",
       " 'JBSS3.SA',\n",
       " 'KLBN11.SA',\n",
       " 'LINX3.SA',\n",
       " 'LWSA3.SA',\n",
       " 'MGLU3.SA',\n",
       " 'MRFG3.SA',\n",
       " 'NGRD3.SA',\n",
       " 'NTCO3.SA',\n",
       " 'PETR3.SA',\n",
       " 'PETR4.SA',\n",
       " 'PETZ3.SA',\n",
       " 'PRIO3.SA',\n",
       " 'QUAL3.SA',\n",
       " 'SANB11.SA',\n",
       " 'SLCE3.SA',\n",
       " 'SMLS3.SA',\n",
       " 'SMTO3.SA',\n",
       " 'SUZB3.SA',\n",
       " 'TAEE11.SA',\n",
       " 'TASA4.SA',\n",
       " 'TRPL4.SA',\n",
       " 'USIM5.SA',\n",
       " 'VALE3.SA',\n",
       " 'WEGE3.SA']"
      ]
     },
     "execution_count": 388,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    # Apenas ativos com Sharpe > 0\n",
    "\n",
    "finals_stocks\n",
    "select = finals_stocks.copy()\n",
    "\n",
    "select['Sharpe'] = select['Sharpe'] >= 0\n",
    "\n",
    "select_2 = select.copy()\n",
    "\n",
    "list_append = []\n",
    "for i in range(len(select_2)):\n",
    "        if  select_2.iloc[i]['Sharpe'] == True:\n",
    "            list_append.append(select_2.index[i])\n",
    "\n",
    "best_names = list_append\n",
    "positive_sharp = best_names\n",
    "best_names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Ativos com regressão de retornos ascendentes</h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 389,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['AERI3.SA',\n",
       " 'BIDI4.SA',\n",
       " 'BPAN4.SA',\n",
       " 'BRKM5.SA',\n",
       " 'CASH3.SA',\n",
       " 'CRFB3.SA',\n",
       " 'EMBR3.SA',\n",
       " 'ETER3.SA',\n",
       " 'JBSS3.SA',\n",
       " 'LAVV3.SA',\n",
       " 'NGRD3.SA',\n",
       " 'PCAR3.SA',\n",
       " 'PETZ3.SA',\n",
       " 'SANB11.SA',\n",
       " 'SLCE3.SA',\n",
       " 'SOMA3.SA',\n",
       " 'STBP3.SA',\n",
       " 'TAEE11.SA',\n",
       " 'TASA4.SA',\n",
       " 'TOTS3.SA']"
      ]
     },
     "execution_count": 389,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    # Apenas ativos com coeficiente linear de retornos > 0 \n",
    "\n",
    "finals_stocks\n",
    "select = finals_stocks.copy()\n",
    "\n",
    "select['Coef_int'] = select['Coef_int'] >= 0\n",
    "\n",
    "select_2 = select.copy()\n",
    "\n",
    "list_append = []\n",
    "for i in range(len(select_2)):\n",
    "        if(select_2.iloc[i]['Coef_int'] == True):\n",
    "            list_append.append(select_2.index[i])\n",
    "\n",
    "best_names = list_append\n",
    "coef_int_list = best_names\n",
    "best_names\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Ativos em reversao de tendencia de baixa da regressao de retornos</h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 390,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['BPAN4.SA',\n",
       " 'CASH3.SA',\n",
       " 'CRFB3.SA',\n",
       " 'EMBR3.SA',\n",
       " 'JBSS3.SA',\n",
       " 'LAVV3.SA',\n",
       " 'NGRD3.SA',\n",
       " 'PCAR3.SA',\n",
       " 'SOMA3.SA',\n",
       " 'STBP3.SA',\n",
       " 'TOTS3.SA']"
      ]
     },
     "execution_count": 390,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    # Apenas ativos com coeficiente linear de retornos > 0 \n",
    "\n",
    "finals_stocks\n",
    "select = finals_stocks.copy()\n",
    "\n",
    "select['Coef_int'] = select['Coef_int'] >= 0\n",
    "select['Reg_int'] = select['Reg_int'] < 0 \n",
    "\n",
    "select_2 = select.copy()\n",
    "\n",
    "list_append = []\n",
    "for i in range(len(select_2)):\n",
    "        if(select_2.iloc[i]['Coef_int'] == True):\n",
    "            if(select_2.iloc[i]['Reg_int'] == True):\n",
    "                list_append.append(select_2.index[i])\n",
    "\n",
    "best_names = list_append\n",
    "coef_int_list_ideal = best_names\n",
    "best_names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Ativos com regressão de preços ascendentes</h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 391,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ABEV3.SA',\n",
       " 'AERI3.SA',\n",
       " 'ALPA4.SA',\n",
       " 'ANIM3.SA',\n",
       " 'AZUL4.SA',\n",
       " 'BIDI4.SA',\n",
       " 'BMGB4.SA',\n",
       " 'BPAN4.SA',\n",
       " 'BRAP4.SA',\n",
       " 'BRFS3.SA',\n",
       " 'BRKM5.SA',\n",
       " 'CAML3.SA',\n",
       " 'CASH3.SA',\n",
       " 'CEAB3.SA',\n",
       " 'CPFE3.SA',\n",
       " 'CSAN3.SA',\n",
       " 'CSNA3.SA',\n",
       " 'DTEX3.SA',\n",
       " 'ELET3.SA',\n",
       " 'ELET6.SA',\n",
       " 'EMBR3.SA',\n",
       " 'ENAT3.SA',\n",
       " 'ENEV3.SA',\n",
       " 'ENGI11.SA',\n",
       " 'ENJU3.SA',\n",
       " 'ETER3.SA',\n",
       " 'FLRY3.SA',\n",
       " 'GFSA3.SA',\n",
       " 'GGBR4.SA',\n",
       " 'GMAT3.SA',\n",
       " 'GNDI3.SA',\n",
       " 'GOAU4.SA',\n",
       " 'GOLL4.SA',\n",
       " 'GRND3.SA',\n",
       " 'HAPV3.SA',\n",
       " 'HBSA3.SA',\n",
       " 'HYPE3.SA',\n",
       " 'JBSS3.SA',\n",
       " 'KLBN11.SA',\n",
       " 'KLBN4.SA',\n",
       " 'LAVV3.SA',\n",
       " 'LINX3.SA',\n",
       " 'LJQQ3.SA',\n",
       " 'LWSA3.SA',\n",
       " 'MEAL3.SA',\n",
       " 'MGLU3.SA',\n",
       " 'MILS3.SA',\n",
       " 'MRFG3.SA',\n",
       " 'MYPK3.SA',\n",
       " 'NGRD3.SA',\n",
       " 'NTCO3.SA',\n",
       " 'OIBR3.SA',\n",
       " 'OIBR4.SA',\n",
       " 'PETR3.SA',\n",
       " 'PETR4.SA',\n",
       " 'PETZ3.SA',\n",
       " 'POSI3.SA',\n",
       " 'PRIO3.SA',\n",
       " 'PTBL3.SA',\n",
       " 'QUAL3.SA',\n",
       " 'RADL3.SA',\n",
       " 'RANI3.SA',\n",
       " 'SANB11.SA',\n",
       " 'SLCE3.SA',\n",
       " 'SMLS3.SA',\n",
       " 'SMTO3.SA',\n",
       " 'SOMA3.SA',\n",
       " 'STBP3.SA',\n",
       " 'SUZB3.SA',\n",
       " 'TAEE11.SA',\n",
       " 'TASA4.SA',\n",
       " 'TIET11.SA',\n",
       " 'TOTS3.SA',\n",
       " 'TRPL4.SA',\n",
       " 'USIM5.SA',\n",
       " 'VALE3.SA',\n",
       " 'VVAR3.SA',\n",
       " 'WEGE3.SA',\n",
       " 'YDUQ3.SA']"
      ]
     },
     "execution_count": 391,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    # Apenas ativos com coeficiente linear de preço > 0 \n",
    "\n",
    "finals_stocks\n",
    "select = finals_stocks.copy()\n",
    "\n",
    "select['Coef_price'] = select['Coef_price'] >= 0\n",
    "\n",
    "select_2 = select.copy()\n",
    "\n",
    "list_append = []\n",
    "for i in range(len(select_2)):\n",
    "        if(select_2.iloc[i]['Coef_price'] == True):\n",
    "            list_append.append(select_2.index[i])\n",
    "\n",
    "best_names = list_append\n",
    "coef_price_list = best_names\n",
    "best_names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Ativos com regressão de preços e retornos ascendentes</h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 392,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['AERI3.SA',\n",
       " 'BIDI4.SA',\n",
       " 'BPAN4.SA',\n",
       " 'BRKM5.SA',\n",
       " 'CASH3.SA',\n",
       " 'EMBR3.SA',\n",
       " 'ETER3.SA',\n",
       " 'JBSS3.SA',\n",
       " 'LAVV3.SA',\n",
       " 'NGRD3.SA',\n",
       " 'PETZ3.SA',\n",
       " 'SANB11.SA',\n",
       " 'SLCE3.SA',\n",
       " 'SOMA3.SA',\n",
       " 'STBP3.SA',\n",
       " 'TAEE11.SA',\n",
       " 'TASA4.SA',\n",
       " 'TOTS3.SA']"
      ]
     },
     "execution_count": 392,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    # Apenas ativos com coeficiente linear de retornos e preco > 0 \n",
    "\n",
    "finals_stocks\n",
    "select = finals_stocks.copy()\n",
    "\n",
    "select['Coef_price'] = select['Coef_price'] >= 0\n",
    "select['Coef_int'] = select['Coef_int'] >= 0\n",
    "\n",
    "select_2 = select.copy()\n",
    "\n",
    "list_append = []\n",
    "for i in range(len(select_2)):\n",
    "        if(select_2.iloc[i]['Coef_int'] & select_2.iloc[i]['Coef_price'] == True):\n",
    "            list_append.append(select_2.index[i])\n",
    "\n",
    "best_names = list_append\n",
    "coef_price_int = best_names\n",
    "best_names\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Ativos com pontuação AAA</h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 393,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['AERI3.SA',\n",
       " 'BIDI4.SA',\n",
       " 'CASH3.SA',\n",
       " 'ETER3.SA',\n",
       " 'NGRD3.SA',\n",
       " 'PETZ3.SA',\n",
       " 'SANB11.SA',\n",
       " 'SLCE3.SA',\n",
       " 'TAEE11.SA',\n",
       " 'TASA4.SA']"
      ]
     },
     "execution_count": 393,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    # Apenas ativos com Coeficiente Linear > 0, Sharpe e Preço \n",
    "\n",
    "finals_stocks\n",
    "select = finals_stocks.copy()\n",
    "\n",
    "select['Coef_price'] = select['Coef_price'] >= 0\n",
    "select['Coef_int'] = select['Coef_int'] >= 0\n",
    "select['Sharpe'] = select['Sharpe'] >= 0\n",
    "\n",
    "select_2 = select.copy()\n",
    "\n",
    "list_append = []\n",
    "for i in range(len(select_2)):\n",
    "        if select_2.iloc[i]['Coef_price'] & select_2.iloc[i]['Coef_int'] == True:\n",
    "            if  select_2.iloc[i]['Sharpe'] == True:\n",
    "                if  select_2.iloc[i]['Actual_price'] < select_2.iloc[i]['Target_sell']:\n",
    "                    if select_2.iloc[i]['Actual_price'] > select_2.iloc[i]['Target_buy']:\n",
    "                        list_append.append(select_2.index[i])\n",
    "\n",
    "best_names = list_append\n",
    "coef_price_int_sharp = best_names\n",
    "best_names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Ativos com pontuação máxima de critérios</h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 394,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['CASH3.SA', 'NGRD3.SA']"
      ]
     },
     "execution_count": 394,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "finals_stocks\n",
    "select = finals_stocks.copy()\n",
    "\n",
    "select['Coef_price'] = select['Coef_price'] >= 0\n",
    "select['Coef_int'] = select['Coef_int'] >= 0\n",
    "select['Reg_int'] = select['Reg_int'] < 0 \n",
    "select['Sharpe'] = select['Sharpe'] >= 0\n",
    "\n",
    "select_2 = select.copy()\n",
    "\n",
    "list_append = []\n",
    "for i in range(len(select_2)):\n",
    "        if select_2.iloc[i]['Coef_price'] & select_2.iloc[i]['Coef_int'] == True:\n",
    "            if select_2.iloc[i]['Reg_int'] == True:\n",
    "                if  select_2.iloc[i]['Sharpe'] == True:\n",
    "                    if  select_2.iloc[i]['Actual_price'] < select_2.iloc[i]['Target_sell']:\n",
    "                        if select_2.iloc[i]['Actual_price'] > select_2.iloc[i]['Target_buy']:\n",
    "                            list_append.append(select_2.index[i])\n",
    "\n",
    "best_names = list_append\n",
    "best_players = best_names\n",
    "best_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "metadata": {},
   "outputs": [],
   "source": [
    "############################################################################################################"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 401,
   "metadata": {},
   "outputs": [],
   "source": [
    "best_names.remove('BPAN4.SA')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 402,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  23 of 23 downloaded\n"
     ]
    },
    {
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       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"10\" halign=\"left\">Adj Close</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"10\" halign=\"left\">Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>AERI3.SA</th>\n",
       "      <th>BIDI4.SA</th>\n",
       "      <th>BRAP4.SA</th>\n",
       "      <th>BRKM5.SA</th>\n",
       "      <th>CASH3.SA</th>\n",
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       "      <th>DMMO3.SA</th>\n",
       "      <th>ENAT3.SA</th>\n",
       "      <th>ETER3.SA</th>\n",
       "      <th>LWSA3.SA</th>\n",
       "      <th>...</th>\n",
       "      <th>PETZ3.SA</th>\n",
       "      <th>PRIO3.SA</th>\n",
       "      <th>RANI3.SA</th>\n",
       "      <th>SLCE3.SA</th>\n",
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       "      <th>TAEE11.SA</th>\n",
       "      <th>TASA4.SA</th>\n",
       "      <th>USIM5.SA</th>\n",
       "      <th>VALE3.SA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-03-22</th>\n",
       "      <td>9.28</td>\n",
       "      <td>51.39</td>\n",
       "      <td>62.06</td>\n",
       "      <td>36.96</td>\n",
       "      <td>24.01</td>\n",
       "      <td>35.00</td>\n",
       "      <td>0.89</td>\n",
       "      <td>15.70</td>\n",
       "      <td>17.00</td>\n",
       "      <td>24.81</td>\n",
       "      <td>...</td>\n",
       "      <td>2694000.0</td>\n",
       "      <td>5539000</td>\n",
       "      <td>1663000</td>\n",
       "      <td>1016800</td>\n",
       "      <td>1222500</td>\n",
       "      <td>5230200</td>\n",
       "      <td>2723400</td>\n",
       "      <td>4910800</td>\n",
       "      <td>15160400</td>\n",
       "      <td>21120800</td>\n",
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       "    <tr>\n",
       "      <th>2021-03-23</th>\n",
       "      <td>8.94</td>\n",
       "      <td>55.58</td>\n",
       "      <td>61.25</td>\n",
       "      <td>36.67</td>\n",
       "      <td>23.88</td>\n",
       "      <td>33.50</td>\n",
       "      <td>0.88</td>\n",
       "      <td>15.02</td>\n",
       "      <td>17.80</td>\n",
       "      <td>24.74</td>\n",
       "      <td>...</td>\n",
       "      <td>1314200.0</td>\n",
       "      <td>6832700</td>\n",
       "      <td>1435700</td>\n",
       "      <td>1055400</td>\n",
       "      <td>1003200</td>\n",
       "      <td>5040500</td>\n",
       "      <td>2363300</td>\n",
       "      <td>3630800</td>\n",
       "      <td>24778900</td>\n",
       "      <td>20518500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-24</th>\n",
       "      <td>9.02</td>\n",
       "      <td>53.79</td>\n",
       "      <td>61.66</td>\n",
       "      <td>37.34</td>\n",
       "      <td>22.70</td>\n",
       "      <td>33.30</td>\n",
       "      <td>0.87</td>\n",
       "      <td>15.49</td>\n",
       "      <td>18.75</td>\n",
       "      <td>24.10</td>\n",
       "      <td>...</td>\n",
       "      <td>2318400.0</td>\n",
       "      <td>7956300</td>\n",
       "      <td>1747600</td>\n",
       "      <td>1303700</td>\n",
       "      <td>1082200</td>\n",
       "      <td>9830500</td>\n",
       "      <td>2254700</td>\n",
       "      <td>3277200</td>\n",
       "      <td>20622300</td>\n",
       "      <td>24726000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-25</th>\n",
       "      <td>9.20</td>\n",
       "      <td>51.47</td>\n",
       "      <td>61.85</td>\n",
       "      <td>37.77</td>\n",
       "      <td>22.40</td>\n",
       "      <td>33.47</td>\n",
       "      <td>0.87</td>\n",
       "      <td>15.58</td>\n",
       "      <td>18.17</td>\n",
       "      <td>23.50</td>\n",
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       "      <td>1644800.0</td>\n",
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       "      <td>2138000</td>\n",
       "      <td>18936600</td>\n",
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       "    <tr>\n",
       "      <th>2021-03-26</th>\n",
       "      <td>9.10</td>\n",
       "      <td>50.98</td>\n",
       "      <td>65.37</td>\n",
       "      <td>37.83</td>\n",
       "      <td>23.02</td>\n",
       "      <td>35.14</td>\n",
       "      <td>0.87</td>\n",
       "      <td>15.48</td>\n",
       "      <td>18.50</td>\n",
       "      <td>23.00</td>\n",
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       "      <td>1025700</td>\n",
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       "      <td>1758100</td>\n",
       "      <td>5120100</td>\n",
       "      <td>1618600</td>\n",
       "      <td>1443600</td>\n",
       "      <td>18165600</td>\n",
       "      <td>23056100</td>\n",
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       "</table>\n",
       "<p>5 rows × 138 columns</p>\n",
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      ],
      "text/plain": [
       "           Adj Close                                                        \\\n",
       "            AERI3.SA BIDI4.SA BRAP4.SA BRKM5.SA CASH3.SA CSNA3.SA DMMO3.SA   \n",
       "Date                                                                         \n",
       "2021-03-22      9.28    51.39    62.06    36.96    24.01    35.00     0.89   \n",
       "2021-03-23      8.94    55.58    61.25    36.67    23.88    33.50     0.88   \n",
       "2021-03-24      9.02    53.79    61.66    37.34    22.70    33.30     0.87   \n",
       "2021-03-25      9.20    51.47    61.85    37.77    22.40    33.47     0.87   \n",
       "2021-03-26      9.10    50.98    65.37    37.83    23.02    35.14     0.87   \n",
       "\n",
       "                                       ...     Volume                    \\\n",
       "           ENAT3.SA ETER3.SA LWSA3.SA  ...   PETZ3.SA PRIO3.SA RANI3.SA   \n",
       "Date                                   ...                                \n",
       "2021-03-22    15.70    17.00    24.81  ...  2694000.0  5539000  1663000   \n",
       "2021-03-23    15.02    17.80    24.74  ...  1314200.0  6832700  1435700   \n",
       "2021-03-24    15.49    18.75    24.10  ...  2318400.0  7956300  1747600   \n",
       "2021-03-25    15.58    18.17    23.50  ...  1644800.0  7519400  1055500   \n",
       "2021-03-26    15.48    18.50    23.00  ...  2516800.0  9026700  1025700   \n",
       "\n",
       "                                                                              \n",
       "           SLCE3.SA SMTO3.SA SUZB3.SA TAEE11.SA TASA4.SA  USIM5.SA  VALE3.SA  \n",
       "Date                                                                          \n",
       "2021-03-22  1016800  1222500  5230200   2723400  4910800  15160400  21120800  \n",
       "2021-03-23  1055400  1003200  5040500   2363300  3630800  24778900  20518500  \n",
       "2021-03-24  1303700  1082200  9830500   2254700  3277200  20622300  24726000  \n",
       "2021-03-25   542000  2662300  8424900   2390500  2138000  18936600  23644400  \n",
       "2021-03-26   725300  1758100  5120100   1618600  1443600  18165600  23056100  \n",
       "\n",
       "[5 rows x 138 columns]"
      ]
     },
     "execution_count": 402,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Analise dos ativos filtrados\n",
    "stocks_all=yahoo(best_names,S_Day, S_Month, S_Year, E_Day, E_Month, E_Year)\n",
    "stocks_all.tail()\n",
    "\n",
    "index = stocks_all.index\n",
    "stocks_close = stocks_all['Adj Close']\n",
    "stocks_all.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 403,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Date</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-03-30</th>\n",
       "      <td>NaN</td>\n",
       "      <td>10.75</td>\n",
       "      <td>27.40</td>\n",
       "      <td>17.70</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.05</td>\n",
       "      <td>0.6399</td>\n",
       "      <td>7.80</td>\n",
       "      <td>2.64</td>\n",
       "      <td>4.58</td>\n",
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       "      <td>14900</td>\n",
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       "      <td>1948800</td>\n",
       "      <td>1138500</td>\n",
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       "    <tr>\n",
       "      <th>2020-03-31</th>\n",
       "      <td>NaN</td>\n",
       "      <td>10.53</td>\n",
       "      <td>27.97</td>\n",
       "      <td>17.22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.97</td>\n",
       "      <td>0.6199</td>\n",
       "      <td>8.10</td>\n",
       "      <td>2.40</td>\n",
       "      <td>4.49</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5092100</td>\n",
       "      <td>62700</td>\n",
       "      <td>869800</td>\n",
       "      <td>1686000</td>\n",
       "      <td>9876700</td>\n",
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       "      <td>1789900</td>\n",
       "      <td>20621100</td>\n",
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       "    <tr>\n",
       "      <th>2020-04-01</th>\n",
       "      <td>NaN</td>\n",
       "      <td>10.19</td>\n",
       "      <td>28.06</td>\n",
       "      <td>16.27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.83</td>\n",
       "      <td>0.5599</td>\n",
       "      <td>7.45</td>\n",
       "      <td>2.41</td>\n",
       "      <td>3.74</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>25900</td>\n",
       "      <td>1641200</td>\n",
       "      <td>1209800</td>\n",
       "      <td>10785000</td>\n",
       "      <td>2706500</td>\n",
       "      <td>1550700</td>\n",
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       "      <th>2020-04-02</th>\n",
       "      <td>NaN</td>\n",
       "      <td>10.43</td>\n",
       "      <td>27.80</td>\n",
       "      <td>16.87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.96</td>\n",
       "      <td>0.5999</td>\n",
       "      <td>7.87</td>\n",
       "      <td>2.19</td>\n",
       "      <td>3.61</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2020-04-03</th>\n",
       "      <td>NaN</td>\n",
       "      <td>9.29</td>\n",
       "      <td>25.82</td>\n",
       "      <td>15.62</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.24</td>\n",
       "      <td>0.5899</td>\n",
       "      <td>7.79</td>\n",
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       "      <td>4.17</td>\n",
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       "      <td>14609500</td>\n",
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       "      <td>790400</td>\n",
       "      <td>32839000</td>\n",
       "      <td>31650000</td>\n",
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       "</table>\n",
       "<p>5 rows × 138 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Adj Close                                                        \\\n",
       "            AERI3.SA BIDI4.SA BRAP4.SA BRKM5.SA CASH3.SA CSNA3.SA DMMO3.SA   \n",
       "Date                                                                         \n",
       "2020-03-30       NaN    10.75    27.40    17.70      NaN     7.05   0.6399   \n",
       "2020-03-31       NaN    10.53    27.97    17.22      NaN     6.97   0.6199   \n",
       "2020-04-01       NaN    10.19    28.06    16.27      NaN     6.83   0.5599   \n",
       "2020-04-02       NaN    10.43    27.80    16.87      NaN     6.96   0.5999   \n",
       "2020-04-03       NaN     9.29    25.82    15.62      NaN     6.24   0.5899   \n",
       "\n",
       "                                       ...   Volume                    \\\n",
       "           ENAT3.SA ETER3.SA LWSA3.SA  ... PETZ3.SA PRIO3.SA RANI3.SA   \n",
       "Date                                   ...                              \n",
       "2020-03-30     7.80     2.64     4.58  ...      NaN  6170400    14900   \n",
       "2020-03-31     8.10     2.40     4.49  ...      NaN  5092100    62700   \n",
       "2020-04-01     7.45     2.41     3.74  ...      NaN  3925100    25900   \n",
       "2020-04-02     7.87     2.19     3.61  ...      NaN  9727000    13400   \n",
       "2020-04-03     7.79     2.20     4.17  ...      NaN  9578200    18300   \n",
       "\n",
       "                                                                               \n",
       "           SLCE3.SA SMTO3.SA  SUZB3.SA TAEE11.SA TASA4.SA  USIM5.SA  VALE3.SA  \n",
       "Date                                                                           \n",
       "2020-03-30  1182000   668000  10422100   1948800  1138500  13666100  31298300  \n",
       "2020-03-31   869800  1686000   9876700   2426100  1789900  20621100  39238000  \n",
       "2020-04-01  1641200  1209800  10785000   2706500  1550700  12790300  37092100  \n",
       "2020-04-02  2389000  3187500  14377500   3710300  1423300  20488600  34372600  \n",
       "2020-04-03  1222100  2789300  14609500   5383600   790400  32839000  31650000  \n",
       "\n",
       "[5 rows x 138 columns]"
      ]
     },
     "execution_count": 403,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stocks_all.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 404,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Insira a taxa de comparação para o Sharpe:\n",
      "\n",
      "===========> AERI3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  44\n",
      "              Negative -  43\n",
      "              Pct Up   - 50.57\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  2\n",
      "              Negative -  2\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.345\n",
      "\n",
      "              R. price    : -3.37974\n",
      "              Coef_price  : 0.05621559\n",
      "\n",
      "              R. intercept: 0.00024\n",
      "              Coef        : 0.00001362\n",
      "\n",
      "              Target_sell : 9.48\n",
      "              Actual_price: 9.10\n",
      "              Target_buy  : 8.97\n",
      "\n",
      "              Base_price  : 2.86\n",
      "              Stop_loss   : -68.57%\n",
      "\n",
      "              Stock_return: 49.18%\n",
      "\n",
      "\n",
      "===========> BIDI4.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  137\n",
      "              Negative -  106\n",
      "              Pct Up   - 56.38\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  10\n",
      "              Negative -  2\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.989\n",
      "\n",
      "              R. price    : 2.66825\n",
      "              Coef_price  : 0.18006328\n",
      "\n",
      "              R. intercept: 0.00448\n",
      "              Coef        : 0.00002293\n",
      "\n",
      "              Target_sell : 56.85\n",
      "              Actual_price: 50.98\n",
      "              Target_buy  : 47.37\n",
      "\n",
      "              Base_price  : 26.82\n",
      "              Stop_loss   : -47.38%\n",
      "\n",
      "              Stock_return: 374.23%\n",
      "\n",
      "\n",
      "===========> BRAP4.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  130\n",
      "              Negative -  113\n",
      "              Pct Up   - 53.50\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  11\n",
      "              Negative -  1\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.930\n",
      "\n",
      "              R. price    : 24.78613\n",
      "              Coef_price  : 0.18517351\n",
      "\n",
      "              R. intercept: 0.00553\n",
      "              Coef        : -0.00001377\n",
      "\n",
      "              Target_sell : 68.58\n",
      "              Actual_price: 65.37\n",
      "              Target_buy  : 57.02\n",
      "\n",
      "              Base_price  : 45.08\n",
      "              Stop_loss   : -31.04%\n",
      "\n",
      "              Stock_return: 138.58%\n",
      "\n",
      "\n",
      "===========> BRKM5.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  120\n",
      "              Negative -  123\n",
      "              Pct Up   - 49.38\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  9\n",
      "              Negative -  3\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 1.358\n",
      "\n",
      "              R. price    : 20.36896\n",
      "              Coef_price  : 0.03366808\n",
      "\n",
      "              R. intercept: 0.00274\n",
      "              Coef        : 0.00000849\n",
      "\n",
      "              Target_sell : 37.74\n",
      "              Actual_price: 37.83\n",
      "              Target_buy  : 36.49\n",
      "\n",
      "              Base_price  : 29.10\n",
      "              Stop_loss   : -23.08%\n",
      "\n",
      "              Stock_return: 113.73%\n",
      "\n",
      "\n",
      "===========> CASH3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  52\n",
      "              Negative -  38\n",
      "              Pct Up   - 57.78\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  3\n",
      "              Negative -  1\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 1.564\n",
      "\n",
      "              R. price    : -8.21340\n",
      "              Coef_price  : 0.13071513\n",
      "\n",
      "              R. intercept: -0.00162\n",
      "              Coef        : 0.00004905\n",
      "\n",
      "              Target_sell : 25.13\n",
      "              Actual_price: 23.02\n",
      "              Target_buy  : 22.09\n",
      "\n",
      "              Base_price  : 7.40\n",
      "              Stop_loss   : -67.84%\n",
      "\n",
      "              Stock_return: 142.57%\n",
      "\n",
      "\n",
      "===========> CSNA3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  131\n",
      "              Negative -  112\n",
      "              Pct Up   - 53.91\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  10\n",
      "              Negative -  2\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.875\n",
      "\n",
      "              R. price    : 2.94603\n",
      "              Coef_price  : 0.13713546\n",
      "\n",
      "              R. intercept: 0.00955\n",
      "              Coef        : -0.00001809\n",
      "\n",
      "              Target_sell : 37.05\n",
      "              Actual_price: 35.14\n",
      "              Target_buy  : 32.38\n",
      "\n",
      "              Base_price  : 19.04\n",
      "              Stop_loss   : -45.81%\n",
      "\n",
      "              Stock_return: 398.44%\n",
      "\n",
      "\n",
      "===========> DMMO3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  112\n",
      "              Negative -  131\n",
      "              Pct Up   - 46.09\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -10.961\n",
      "\n",
      "              R. price    : 1.37019\n",
      "              Coef_price  : -0.00118852\n",
      "\n",
      "              R. intercept: 0.01830\n",
      "              Coef        : -0.00012151\n",
      "\n",
      "              Target_sell : 0.88\n",
      "              Actual_price: 0.87\n",
      "              Target_buy  : 0.88\n",
      "\n",
      "              Base_price  : 1.12\n",
      "              Stop_loss   : 28.74%\n",
      "\n",
      "              Stock_return: 35.96%\n",
      "\n",
      "\n",
      "===========> ENAT3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  123\n",
      "              Negative -  120\n",
      "              Pct Up   - 50.62\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  7\n",
      "              Negative -  5\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.231\n",
      "\n",
      "              R. price    : 8.88893\n",
      "              Coef_price  : 0.01826695\n",
      "\n",
      "              R. intercept: 0.00358\n",
      "              Coef        : -0.00000211\n",
      "\n",
      "              Target_sell : 15.69\n",
      "              Actual_price: 15.48\n",
      "              Target_buy  : 15.41\n",
      "\n",
      "              Base_price  : 12.18\n",
      "              Stop_loss   : -21.29%\n",
      "\n",
      "              Stock_return: 98.46%\n",
      "\n",
      "\n",
      "===========> ETER3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  138\n",
      "              Negative -  105\n",
      "              Pct Up   - 56.79\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  9\n",
      "              Negative -  3\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.762\n",
      "\n",
      "              R. price    : 0.25433\n",
      "              Coef_price  : 0.06509284\n",
      "\n",
      "              R. intercept: 0.00764\n",
      "              Coef        : 0.00001396\n",
      "\n",
      "              Target_sell : 18.72\n",
      "              Actual_price: 18.50\n",
      "              Target_buy  : 17.55\n",
      "\n",
      "              Base_price  : 9.38\n",
      "              Stop_loss   : -49.31%\n",
      "\n",
      "              Stock_return: 600.76%\n",
      "\n",
      "\n",
      "===========> LWSA3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  136\n",
      "              Negative -  107\n",
      "              Pct Up   - 55.97\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  10\n",
      "              Negative -  2\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.655\n",
      "\n",
      "              R. price    : 3.47481\n",
      "              Coef_price  : 0.09866982\n",
      "\n",
      "              R. intercept: 0.01416\n",
      "              Coef        : -0.00005512\n",
      "\n",
      "              Target_sell : 25.33\n",
      "              Actual_price: 23.00\n",
      "              Target_buy  : 22.96\n",
      "\n",
      "              Base_price  : 13.24\n",
      "              Stop_loss   : -42.45%\n",
      "\n",
      "              Stock_return: 402.18%\n",
      "\n",
      "\n",
      "===========> MRFG3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  127\n",
      "              Negative -  116\n",
      "              Pct Up   - 52.26\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.266\n",
      "\n",
      "              R. price    : 12.35016\n",
      "              Coef_price  : 0.01451198\n",
      "\n",
      "              R. intercept: 0.00633\n",
      "              Coef        : -0.00002807\n",
      "\n",
      "              Target_sell : 16.77\n",
      "              Actual_price: 16.84\n",
      "              Target_buy  : 16.53\n",
      "\n",
      "              Base_price  : 14.59\n",
      "              Stop_loss   : -13.33%\n",
      "\n",
      "              Stock_return: 88.16%\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "===========> NGRD3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  35\n",
      "              Negative -  26\n",
      "              Pct Up   - 57.38\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  2\n",
      "              Negative -  1\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 1.603\n",
      "\n",
      "              R. price    : -2.60733\n",
      "              Coef_price  : 0.03883755\n",
      "\n",
      "              R. intercept: -0.00116\n",
      "              Coef        : 0.00002955\n",
      "\n",
      "              Target_sell : 8.08\n",
      "              Actual_price: 7.87\n",
      "              Target_buy  : 7.78\n",
      "\n",
      "              Base_price  : 2.63\n",
      "              Stop_loss   : -66.57%\n",
      "\n",
      "              Stock_return: 59.31%\n",
      "\n",
      "\n",
      "===========> OIBR4.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  122\n",
      "              Negative -  121\n",
      "              Pct Up   - 50.21\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -3.026\n",
      "\n",
      "              R. price    : 1.16652\n",
      "              Coef_price  : 0.00802499\n",
      "\n",
      "              R. intercept: 0.01207\n",
      "              Coef        : -0.00005939\n",
      "\n",
      "              Target_sell : 2.38\n",
      "              Actual_price: 2.36\n",
      "              Target_buy  : 2.36\n",
      "\n",
      "              Base_price  : 1.76\n",
      "              Stop_loss   : -25.29%\n",
      "\n",
      "              Stock_return: 145.83%\n",
      "\n",
      "\n",
      "===========> PETZ3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  67\n",
      "              Negative -  60\n",
      "              Pct Up   - 52.76\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  5\n",
      "              Negative -  1\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.102\n",
      "\n",
      "              R. price    : -5.18268\n",
      "              Coef_price  : 0.12400335\n",
      "\n",
      "              R. intercept: 0.00051\n",
      "              Coef        : 0.00000475\n",
      "\n",
      "              Target_sell : 21.23\n",
      "              Actual_price: 19.29\n",
      "              Target_buy  : 18.76\n",
      "\n",
      "              Base_price  : 7.05\n",
      "              Stop_loss   : -63.43%\n",
      "\n",
      "              Stock_return: 24.69%\n",
      "\n",
      "\n",
      "===========> PRIO3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  116\n",
      "              Negative -  127\n",
      "              Pct Up   - 47.74\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 1.298\n",
      "\n",
      "              R. price    : 14.03550\n",
      "              Coef_price  : 0.27464476\n",
      "\n",
      "              R. intercept: 0.01062\n",
      "              Coef        : -0.00002054\n",
      "\n",
      "              Target_sell : 102.44\n",
      "              Actual_price: 92.50\n",
      "              Target_buy  : 77.86\n",
      "\n",
      "              Base_price  : 53.27\n",
      "              Stop_loss   : -42.41%\n",
      "\n",
      "              Stock_return: 444.12%\n",
      "\n",
      "\n",
      "===========> RANI3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  132\n",
      "              Negative -  111\n",
      "              Pct Up   - 54.32\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : -1.638\n",
      "\n",
      "              R. price    : 3.23202\n",
      "              Coef_price  : 0.01186592\n",
      "\n",
      "              R. intercept: 0.00873\n",
      "              Coef        : -0.00004001\n",
      "\n",
      "              Target_sell : 5.69\n",
      "              Actual_price: 5.60\n",
      "              Target_buy  : 5.63\n",
      "\n",
      "              Base_price  : 4.42\n",
      "              Stop_loss   : -21.14%\n",
      "\n",
      "              Stock_return: 104.38%\n",
      "\n",
      "\n",
      "===========> SLCE3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  127\n",
      "              Negative -  116\n",
      "              Pct Up   - 52.26\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  9\n",
      "              Negative -  3\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.950\n",
      "\n",
      "              R. price    : 18.69027\n",
      "              Coef_price  : 0.07379525\n",
      "\n",
      "              R. intercept: 0.00052\n",
      "              Coef        : 0.00002112\n",
      "\n",
      "              Target_sell : 42.89\n",
      "              Actual_price: 42.47\n",
      "              Target_buy  : 39.82\n",
      "\n",
      "              Base_price  : 30.58\n",
      "              Stop_loss   : -28.00%\n",
      "\n",
      "              Stock_return: 99.48%\n",
      "\n",
      "\n",
      "===========> SMTO3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  131\n",
      "              Negative -  112\n",
      "              Pct Up   - 53.91\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.581\n",
      "\n",
      "              R. price    : 15.95960\n",
      "              Coef_price  : 0.06313793\n",
      "\n",
      "              R. intercept: 0.00530\n",
      "              Coef        : -0.00001947\n",
      "\n",
      "              Target_sell : 30.56\n",
      "              Actual_price: 28.91\n",
      "              Target_buy  : 28.71\n",
      "\n",
      "              Base_price  : 22.43\n",
      "              Stop_loss   : -22.40%\n",
      "\n",
      "              Stock_return: 87.73%\n",
      "\n",
      "\n",
      "===========> SUZB3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  126\n",
      "              Negative -  117\n",
      "              Pct Up   - 51.85\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  9\n",
      "              Negative -  3\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 1.110\n",
      "\n",
      "              R. price    : 32.07331\n",
      "              Coef_price  : 0.15277986\n",
      "\n",
      "              R. intercept: 0.00347\n",
      "              Coef        : 0.00000005\n",
      "\n",
      "              Target_sell : 78.78\n",
      "              Actual_price: 72.50\n",
      "              Target_buy  : 67.67\n",
      "\n",
      "              Base_price  : 52.29\n",
      "              Stop_loss   : -27.88%\n",
      "\n",
      "              Stock_return: 113.30%\n",
      "\n",
      "\n",
      "===========> TAEE11.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  126\n",
      "              Negative -  117\n",
      "              Pct Up   - 51.85\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.809\n",
      "\n",
      "              R. price    : 23.36916\n",
      "              Coef_price  : 0.04395852\n",
      "\n",
      "              R. intercept: 0.00184\n",
      "              Coef        : 0.00000118\n",
      "\n",
      "              Target_sell : 36.46\n",
      "              Actual_price: 36.10\n",
      "              Target_buy  : 34.88\n",
      "\n",
      "              Base_price  : 29.73\n",
      "              Stop_loss   : -17.63%\n",
      "\n",
      "              Stock_return: 58.89%\n",
      "\n",
      "\n",
      "===========> TASA4.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  127\n",
      "              Negative -  116\n",
      "              Pct Up   - 52.26\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  10\n",
      "              Negative -  2\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.825\n",
      "\n",
      "              R. price    : 0.70677\n",
      "              Coef_price  : 0.07887533\n",
      "\n",
      "              R. intercept: 0.00622\n",
      "              Coef        : 0.00001726\n",
      "\n",
      "              Target_sell : 24.30\n",
      "              Actual_price: 22.72\n",
      "              Target_buy  : 22.49\n",
      "\n",
      "              Base_price  : 11.71\n",
      "              Stop_loss   : -48.44%\n",
      "\n",
      "              Stock_return: 475.19%\n",
      "\n",
      "\n",
      "===========> USIM5.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  129\n",
      "              Negative -  114\n",
      "              Pct Up   - 53.09\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  10\n",
      "              Negative -  2\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 0.534\n",
      "\n",
      "              R. price    : 3.72336\n",
      "              Coef_price  : 0.05510053\n",
      "\n",
      "              R. intercept: 0.00797\n",
      "              Coef        : -0.00001792\n",
      "\n",
      "              Target_sell : 17.43\n",
      "              Actual_price: 16.58\n",
      "              Target_buy  : 16.51\n",
      "\n",
      "              Base_price  : 10.15\n",
      "              Stop_loss   : -38.77%\n",
      "\n",
      "              Stock_return: 249.79%\n",
      "\n",
      "\n",
      "===========> VALE3.SA\n",
      "\n",
      "------------------------------------Daily Infos--------------------------------------\n",
      "Count:\n",
      "              Positive -  127\n",
      "              Negative -  116\n",
      "              Pct Up   - 52.26\n",
      "\n",
      "-----------------------------------Monthly Infos-------------------------------------\n",
      "Count:\n",
      "              Positive -  8\n",
      "              Negative -  4\n",
      "\n",
      "\n",
      "-----------------------------------Other Infos---------------------------------------\n",
      "Count:\n",
      "              Sharpe      : 1.130\n",
      "\n",
      "              R. price    : 34.35094\n",
      "              Coef_price  : 0.24696318\n",
      "\n",
      "              R. intercept: 0.00452\n",
      "              Coef        : -0.00000429\n",
      "\n",
      "              Target_sell : 105.41\n",
      "              Actual_price: 95.53\n",
      "              Target_buy  : 82.42\n",
      "\n",
      "              Base_price  : 64.94\n",
      "              Stop_loss   : -32.02%\n",
      "\n",
      "              Stock_return: 148.97%\n",
      "\n"
     ]
    }
   ],
   "source": [
    "finals_stocks = routine(best_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 405,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ativos com Melhor Relação em Cada Cluster: ['VALE3.SA', 'CASH3.SA', 'ETER3.SA', 'CSNA3.SA', 'TAEE11.SA']\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "output = stocks_all['Adj Close']\n",
    "%matplotlib inline \n",
    "from sklearn.cluster import KMeans\n",
    "\n",
    "\n",
    "retornos=100*output.pct_change()\n",
    "stocks=retornos.columns\n",
    "\n",
    "\n",
    "X=100*np.array([[np.std(retornos[sto]),np.mean(retornos[sto])] for sto in stocks])\n",
    "\n",
    "N=5\n",
    "\n",
    "kmeans = KMeans(n_clusters=N, random_state=0).fit(X)\n",
    "y_kmeans = kmeans.predict(X)\n",
    "\n",
    "fig = plt.subplots(figsize=(20,5))\n",
    "\n",
    "ax1=plt.subplot(1,1, 1) \n",
    "ax1.scatter(X[:, 0], X[:, 1], c=y_kmeans, s=50, cmap='viridis')\n",
    "ax1.set_title('Retornos de '+str(len(stocks))+' Ações do Índice Amplo',fontsize=20)\n",
    "ax1.set_xlabel('Risco [%]',fontsize=25)\n",
    "ax1.set_ylabel('Retorno [%]',fontsize=25)\n",
    "\n",
    "centers = kmeans.cluster_centers_\n",
    "plt.scatter(centers[:, 0], centers[:, 1], c='black', s=150, alpha=0.2);\n",
    "\n",
    "best=[]\n",
    "for i in range(N):\n",
    "    ind=retornos[retornos.columns[np.where(y_kmeans==i)[0]]].mean()/retornos[retornos.columns[np.where(y_kmeans==i)[0]]].std()\n",
    "    best.append(ind[ind==np.max(ind)])\n",
    "rb=list(pd.DataFrame(best).columns)\n",
    "print(\"Ativos com Melhor Relação em Cada Cluster:\", rb)\n",
    "\n",
    "for r in rb:\n",
    "    plt.text(X[stocks==r][0][0],X[stocks==r][0][1],r,fontsize=15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 406,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  5 of 5 downloaded\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"5\" halign=\"left\">Adj Close</th>\n",
       "      <th colspan=\"5\" halign=\"left\">Close</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"5\" halign=\"left\">Open</th>\n",
       "      <th colspan=\"5\" halign=\"left\">Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>CASH3.SA</th>\n",
       "      <th>CSNA3.SA</th>\n",
       "      <th>ETER3.SA</th>\n",
       "      <th>TAEE11.SA</th>\n",
       "      <th>VALE3.SA</th>\n",
       "      <th>CASH3.SA</th>\n",
       "      <th>CSNA3.SA</th>\n",
       "      <th>ETER3.SA</th>\n",
       "      <th>TAEE11.SA</th>\n",
       "      <th>VALE3.SA</th>\n",
       "      <th>...</th>\n",
       "      <th>CASH3.SA</th>\n",
       "      <th>CSNA3.SA</th>\n",
       "      <th>ETER3.SA</th>\n",
       "      <th>TAEE11.SA</th>\n",
       "      <th>VALE3.SA</th>\n",
       "      <th>CASH3.SA</th>\n",
       "      <th>CSNA3.SA</th>\n",
       "      <th>ETER3.SA</th>\n",
       "      <th>TAEE11.SA</th>\n",
       "      <th>VALE3.SA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-03-30</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.05</td>\n",
       "      <td>2.64</td>\n",
       "      <td>22.72</td>\n",
       "      <td>38.37</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.06</td>\n",
       "      <td>2.64</td>\n",
       "      <td>25.27</td>\n",
       "      <td>41.77</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.84</td>\n",
       "      <td>2.83</td>\n",
       "      <td>25.66</td>\n",
       "      <td>40.92</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14322900</td>\n",
       "      <td>1542099</td>\n",
       "      <td>1948800</td>\n",
       "      <td>31298300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-31</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6.97</td>\n",
       "      <td>2.40</td>\n",
       "      <td>23.12</td>\n",
       "      <td>39.70</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.98</td>\n",
       "      <td>2.40</td>\n",
       "      <td>25.72</td>\n",
       "      <td>43.22</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.06</td>\n",
       "      <td>2.69</td>\n",
       "      <td>25.30</td>\n",
       "      <td>42.30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16501900</td>\n",
       "      <td>1161587</td>\n",
       "      <td>2426100</td>\n",
       "      <td>39238000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-01</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6.83</td>\n",
       "      <td>2.41</td>\n",
       "      <td>22.84</td>\n",
       "      <td>39.83</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.84</td>\n",
       "      <td>2.41</td>\n",
       "      <td>25.41</td>\n",
       "      <td>43.37</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.63</td>\n",
       "      <td>2.30</td>\n",
       "      <td>25.28</td>\n",
       "      <td>41.81</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9417800</td>\n",
       "      <td>433835</td>\n",
       "      <td>2706500</td>\n",
       "      <td>37092100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-02</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6.96</td>\n",
       "      <td>2.19</td>\n",
       "      <td>23.69</td>\n",
       "      <td>39.29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.97</td>\n",
       "      <td>2.19</td>\n",
       "      <td>26.35</td>\n",
       "      <td>42.78</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.98</td>\n",
       "      <td>2.53</td>\n",
       "      <td>25.51</td>\n",
       "      <td>43.95</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11170000</td>\n",
       "      <td>815841</td>\n",
       "      <td>3710300</td>\n",
       "      <td>34372600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-03</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6.24</td>\n",
       "      <td>2.20</td>\n",
       "      <td>23.82</td>\n",
       "      <td>37.20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.25</td>\n",
       "      <td>2.20</td>\n",
       "      <td>26.50</td>\n",
       "      <td>40.50</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.00</td>\n",
       "      <td>2.19</td>\n",
       "      <td>26.50</td>\n",
       "      <td>42.80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16042700</td>\n",
       "      <td>975703</td>\n",
       "      <td>5383600</td>\n",
       "      <td>31650000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-06</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6.54</td>\n",
       "      <td>2.31</td>\n",
       "      <td>24.36</td>\n",
       "      <td>39.61</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.55</td>\n",
       "      <td>2.31</td>\n",
       "      <td>27.10</td>\n",
       "      <td>43.13</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.68</td>\n",
       "      <td>2.30</td>\n",
       "      <td>27.00</td>\n",
       "      <td>42.60</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10198800</td>\n",
       "      <td>371234</td>\n",
       "      <td>2765800</td>\n",
       "      <td>32019300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-07</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6.94</td>\n",
       "      <td>2.34</td>\n",
       "      <td>24.27</td>\n",
       "      <td>40.21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.95</td>\n",
       "      <td>2.34</td>\n",
       "      <td>27.00</td>\n",
       "      <td>43.78</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.92</td>\n",
       "      <td>2.43</td>\n",
       "      <td>28.12</td>\n",
       "      <td>45.19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16963600</td>\n",
       "      <td>430209</td>\n",
       "      <td>3160500</td>\n",
       "      <td>34191900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-08</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.39</td>\n",
       "      <td>2.40</td>\n",
       "      <td>24.31</td>\n",
       "      <td>39.96</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.41</td>\n",
       "      <td>2.40</td>\n",
       "      <td>27.04</td>\n",
       "      <td>43.51</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.00</td>\n",
       "      <td>2.34</td>\n",
       "      <td>27.01</td>\n",
       "      <td>43.50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11954800</td>\n",
       "      <td>358970</td>\n",
       "      <td>3120200</td>\n",
       "      <td>29464500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-09</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.16</td>\n",
       "      <td>2.48</td>\n",
       "      <td>24.18</td>\n",
       "      <td>39.75</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.17</td>\n",
       "      <td>2.48</td>\n",
       "      <td>26.90</td>\n",
       "      <td>43.28</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.60</td>\n",
       "      <td>2.43</td>\n",
       "      <td>27.22</td>\n",
       "      <td>43.95</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10845800</td>\n",
       "      <td>577274</td>\n",
       "      <td>2474200</td>\n",
       "      <td>29827800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-13</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.31</td>\n",
       "      <td>2.46</td>\n",
       "      <td>24.27</td>\n",
       "      <td>40.94</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.33</td>\n",
       "      <td>2.46</td>\n",
       "      <td>27.00</td>\n",
       "      <td>44.57</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.10</td>\n",
       "      <td>2.49</td>\n",
       "      <td>26.77</td>\n",
       "      <td>43.20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11763100</td>\n",
       "      <td>238993</td>\n",
       "      <td>1859700</td>\n",
       "      <td>22066800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-14</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.42</td>\n",
       "      <td>2.76</td>\n",
       "      <td>24.72</td>\n",
       "      <td>40.90</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.44</td>\n",
       "      <td>2.76</td>\n",
       "      <td>27.50</td>\n",
       "      <td>44.53</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.52</td>\n",
       "      <td>2.48</td>\n",
       "      <td>27.45</td>\n",
       "      <td>45.62</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9863100</td>\n",
       "      <td>1024333</td>\n",
       "      <td>2289600</td>\n",
       "      <td>24713600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-15</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.27</td>\n",
       "      <td>2.75</td>\n",
       "      <td>24.65</td>\n",
       "      <td>39.67</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.29</td>\n",
       "      <td>2.75</td>\n",
       "      <td>27.42</td>\n",
       "      <td>43.19</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.20</td>\n",
       "      <td>2.64</td>\n",
       "      <td>27.29</td>\n",
       "      <td>43.50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10329200</td>\n",
       "      <td>1039477</td>\n",
       "      <td>2208000</td>\n",
       "      <td>28808700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-16</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.42</td>\n",
       "      <td>2.59</td>\n",
       "      <td>24.28</td>\n",
       "      <td>39.27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.44</td>\n",
       "      <td>2.59</td>\n",
       "      <td>27.01</td>\n",
       "      <td>42.76</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.43</td>\n",
       "      <td>2.81</td>\n",
       "      <td>27.62</td>\n",
       "      <td>43.80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12883000</td>\n",
       "      <td>582819</td>\n",
       "      <td>1809200</td>\n",
       "      <td>24442900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-17</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.57</td>\n",
       "      <td>2.64</td>\n",
       "      <td>24.07</td>\n",
       "      <td>40.41</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.59</td>\n",
       "      <td>2.64</td>\n",
       "      <td>26.78</td>\n",
       "      <td>44.00</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.55</td>\n",
       "      <td>2.72</td>\n",
       "      <td>27.32</td>\n",
       "      <td>43.90</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11465300</td>\n",
       "      <td>415492</td>\n",
       "      <td>3419300</td>\n",
       "      <td>23604600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-20</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.30</td>\n",
       "      <td>2.63</td>\n",
       "      <td>24.14</td>\n",
       "      <td>39.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.32</td>\n",
       "      <td>2.63</td>\n",
       "      <td>26.85</td>\n",
       "      <td>42.46</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.37</td>\n",
       "      <td>2.64</td>\n",
       "      <td>26.54</td>\n",
       "      <td>43.26</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8522900</td>\n",
       "      <td>274933</td>\n",
       "      <td>2422300</td>\n",
       "      <td>29050700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-22</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.32</td>\n",
       "      <td>2.79</td>\n",
       "      <td>24.89</td>\n",
       "      <td>39.40</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.34</td>\n",
       "      <td>2.79</td>\n",
       "      <td>27.69</td>\n",
       "      <td>42.90</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.35</td>\n",
       "      <td>2.61</td>\n",
       "      <td>26.66</td>\n",
       "      <td>42.60</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7547100</td>\n",
       "      <td>839729</td>\n",
       "      <td>2434500</td>\n",
       "      <td>22693600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-23</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.48</td>\n",
       "      <td>2.69</td>\n",
       "      <td>25.15</td>\n",
       "      <td>39.96</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.50</td>\n",
       "      <td>2.69</td>\n",
       "      <td>27.98</td>\n",
       "      <td>43.51</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.35</td>\n",
       "      <td>2.75</td>\n",
       "      <td>27.80</td>\n",
       "      <td>43.29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18280500</td>\n",
       "      <td>1009083</td>\n",
       "      <td>2425100</td>\n",
       "      <td>27171100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-24</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.07</td>\n",
       "      <td>2.48</td>\n",
       "      <td>24.44</td>\n",
       "      <td>40.19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.08</td>\n",
       "      <td>2.48</td>\n",
       "      <td>27.19</td>\n",
       "      <td>43.76</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.39</td>\n",
       "      <td>2.63</td>\n",
       "      <td>27.55</td>\n",
       "      <td>43.37</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20463400</td>\n",
       "      <td>581433</td>\n",
       "      <td>5022000</td>\n",
       "      <td>55165900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-27</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.23</td>\n",
       "      <td>2.68</td>\n",
       "      <td>25.28</td>\n",
       "      <td>40.92</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.25</td>\n",
       "      <td>2.68</td>\n",
       "      <td>28.12</td>\n",
       "      <td>44.55</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.26</td>\n",
       "      <td>2.52</td>\n",
       "      <td>27.19</td>\n",
       "      <td>44.46</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13778300</td>\n",
       "      <td>605642</td>\n",
       "      <td>3256900</td>\n",
       "      <td>25580600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-28</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.79</td>\n",
       "      <td>2.70</td>\n",
       "      <td>25.44</td>\n",
       "      <td>40.97</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.81</td>\n",
       "      <td>2.70</td>\n",
       "      <td>28.30</td>\n",
       "      <td>44.61</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.50</td>\n",
       "      <td>2.78</td>\n",
       "      <td>28.56</td>\n",
       "      <td>45.20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19016300</td>\n",
       "      <td>459323</td>\n",
       "      <td>2261100</td>\n",
       "      <td>25680000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-29</th>\n",
       "      <td>NaN</td>\n",
       "      <td>9.01</td>\n",
       "      <td>2.74</td>\n",
       "      <td>24.90</td>\n",
       "      <td>42.92</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.03</td>\n",
       "      <td>2.74</td>\n",
       "      <td>27.70</td>\n",
       "      <td>46.73</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.06</td>\n",
       "      <td>2.77</td>\n",
       "      <td>28.44</td>\n",
       "      <td>45.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34574500</td>\n",
       "      <td>628250</td>\n",
       "      <td>3182600</td>\n",
       "      <td>33207500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-30</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.94</td>\n",
       "      <td>2.63</td>\n",
       "      <td>24.72</td>\n",
       "      <td>41.20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.96</td>\n",
       "      <td>2.63</td>\n",
       "      <td>27.50</td>\n",
       "      <td>44.86</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.65</td>\n",
       "      <td>2.67</td>\n",
       "      <td>27.35</td>\n",
       "      <td>45.71</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25377300</td>\n",
       "      <td>367288</td>\n",
       "      <td>3868100</td>\n",
       "      <td>25720300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-04</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.22</td>\n",
       "      <td>2.63</td>\n",
       "      <td>24.63</td>\n",
       "      <td>40.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.23</td>\n",
       "      <td>2.63</td>\n",
       "      <td>27.40</td>\n",
       "      <td>43.93</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.58</td>\n",
       "      <td>2.53</td>\n",
       "      <td>27.11</td>\n",
       "      <td>43.70</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17770600</td>\n",
       "      <td>323563</td>\n",
       "      <td>3169900</td>\n",
       "      <td>16994300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-05</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.95</td>\n",
       "      <td>2.62</td>\n",
       "      <td>24.86</td>\n",
       "      <td>40.14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.96</td>\n",
       "      <td>2.62</td>\n",
       "      <td>27.65</td>\n",
       "      <td>43.70</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.40</td>\n",
       "      <td>2.73</td>\n",
       "      <td>27.52</td>\n",
       "      <td>44.45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13641300</td>\n",
       "      <td>338600</td>\n",
       "      <td>2035400</td>\n",
       "      <td>19070600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-06</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.09</td>\n",
       "      <td>2.65</td>\n",
       "      <td>24.81</td>\n",
       "      <td>40.72</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.10</td>\n",
       "      <td>2.65</td>\n",
       "      <td>27.60</td>\n",
       "      <td>44.33</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.02</td>\n",
       "      <td>2.78</td>\n",
       "      <td>27.80</td>\n",
       "      <td>44.19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12166400</td>\n",
       "      <td>289400</td>\n",
       "      <td>1745700</td>\n",
       "      <td>26602700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-07</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.49</td>\n",
       "      <td>2.63</td>\n",
       "      <td>24.29</td>\n",
       "      <td>42.30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.49</td>\n",
       "      <td>2.63</td>\n",
       "      <td>26.85</td>\n",
       "      <td>46.05</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.26</td>\n",
       "      <td>2.67</td>\n",
       "      <td>27.49</td>\n",
       "      <td>45.63</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22482600</td>\n",
       "      <td>206100</td>\n",
       "      <td>3163500</td>\n",
       "      <td>42194300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-08</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.51</td>\n",
       "      <td>2.59</td>\n",
       "      <td>24.47</td>\n",
       "      <td>44.87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.51</td>\n",
       "      <td>2.59</td>\n",
       "      <td>27.05</td>\n",
       "      <td>48.85</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.74</td>\n",
       "      <td>2.65</td>\n",
       "      <td>27.23</td>\n",
       "      <td>47.50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14286000</td>\n",
       "      <td>298400</td>\n",
       "      <td>2131500</td>\n",
       "      <td>33922800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-11</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.02</td>\n",
       "      <td>2.53</td>\n",
       "      <td>24.07</td>\n",
       "      <td>43.84</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.02</td>\n",
       "      <td>2.53</td>\n",
       "      <td>26.60</td>\n",
       "      <td>47.73</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.40</td>\n",
       "      <td>2.52</td>\n",
       "      <td>27.00</td>\n",
       "      <td>48.21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11776700</td>\n",
       "      <td>201300</td>\n",
       "      <td>1981100</td>\n",
       "      <td>24783100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-12</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.88</td>\n",
       "      <td>2.45</td>\n",
       "      <td>23.84</td>\n",
       "      <td>43.59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.88</td>\n",
       "      <td>2.45</td>\n",
       "      <td>26.35</td>\n",
       "      <td>47.46</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.15</td>\n",
       "      <td>2.53</td>\n",
       "      <td>26.75</td>\n",
       "      <td>48.43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11590800</td>\n",
       "      <td>231900</td>\n",
       "      <td>2555200</td>\n",
       "      <td>21806900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-13</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.52</td>\n",
       "      <td>2.48</td>\n",
       "      <td>24.00</td>\n",
       "      <td>44.58</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.52</td>\n",
       "      <td>2.48</td>\n",
       "      <td>26.53</td>\n",
       "      <td>48.54</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.01</td>\n",
       "      <td>2.43</td>\n",
       "      <td>26.31</td>\n",
       "      <td>48.17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12905000</td>\n",
       "      <td>184400</td>\n",
       "      <td>2359300</td>\n",
       "      <td>34159500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-10</th>\n",
       "      <td>29.71</td>\n",
       "      <td>34.39</td>\n",
       "      <td>12.86</td>\n",
       "      <td>32.55</td>\n",
       "      <td>90.62</td>\n",
       "      <td>29.71</td>\n",
       "      <td>34.39</td>\n",
       "      <td>12.86</td>\n",
       "      <td>32.55</td>\n",
       "      <td>94.70</td>\n",
       "      <td>...</td>\n",
       "      <td>31.52</td>\n",
       "      <td>35.95</td>\n",
       "      <td>13.38</td>\n",
       "      <td>32.88</td>\n",
       "      <td>94.66</td>\n",
       "      <td>4369200.0</td>\n",
       "      <td>17540700</td>\n",
       "      <td>1102000</td>\n",
       "      <td>1682300</td>\n",
       "      <td>40318300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-11</th>\n",
       "      <td>28.58</td>\n",
       "      <td>33.02</td>\n",
       "      <td>12.69</td>\n",
       "      <td>32.51</td>\n",
       "      <td>89.09</td>\n",
       "      <td>28.58</td>\n",
       "      <td>33.02</td>\n",
       "      <td>12.69</td>\n",
       "      <td>32.51</td>\n",
       "      <td>93.10</td>\n",
       "      <td>...</td>\n",
       "      <td>29.71</td>\n",
       "      <td>34.83</td>\n",
       "      <td>12.86</td>\n",
       "      <td>32.88</td>\n",
       "      <td>95.47</td>\n",
       "      <td>2634600.0</td>\n",
       "      <td>17174200</td>\n",
       "      <td>900200</td>\n",
       "      <td>1222900</td>\n",
       "      <td>19775900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-12</th>\n",
       "      <td>28.30</td>\n",
       "      <td>32.83</td>\n",
       "      <td>12.55</td>\n",
       "      <td>32.43</td>\n",
       "      <td>89.84</td>\n",
       "      <td>28.30</td>\n",
       "      <td>32.83</td>\n",
       "      <td>12.55</td>\n",
       "      <td>32.43</td>\n",
       "      <td>93.89</td>\n",
       "      <td>...</td>\n",
       "      <td>28.58</td>\n",
       "      <td>32.81</td>\n",
       "      <td>12.70</td>\n",
       "      <td>32.51</td>\n",
       "      <td>93.12</td>\n",
       "      <td>3521000.0</td>\n",
       "      <td>19754000</td>\n",
       "      <td>757500</td>\n",
       "      <td>936000</td>\n",
       "      <td>14760700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-18</th>\n",
       "      <td>27.66</td>\n",
       "      <td>34.16</td>\n",
       "      <td>12.10</td>\n",
       "      <td>31.96</td>\n",
       "      <td>93.20</td>\n",
       "      <td>27.66</td>\n",
       "      <td>34.16</td>\n",
       "      <td>12.10</td>\n",
       "      <td>31.96</td>\n",
       "      <td>97.40</td>\n",
       "      <td>...</td>\n",
       "      <td>28.89</td>\n",
       "      <td>34.81</td>\n",
       "      <td>12.60</td>\n",
       "      <td>32.25</td>\n",
       "      <td>97.36</td>\n",
       "      <td>3036200.0</td>\n",
       "      <td>29101500</td>\n",
       "      <td>708300</td>\n",
       "      <td>1789600</td>\n",
       "      <td>33088500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-19</th>\n",
       "      <td>27.74</td>\n",
       "      <td>35.26</td>\n",
       "      <td>12.23</td>\n",
       "      <td>32.02</td>\n",
       "      <td>93.55</td>\n",
       "      <td>27.74</td>\n",
       "      <td>35.26</td>\n",
       "      <td>12.23</td>\n",
       "      <td>32.02</td>\n",
       "      <td>97.77</td>\n",
       "      <td>...</td>\n",
       "      <td>27.66</td>\n",
       "      <td>34.17</td>\n",
       "      <td>12.10</td>\n",
       "      <td>31.94</td>\n",
       "      <td>97.21</td>\n",
       "      <td>2009700.0</td>\n",
       "      <td>15722600</td>\n",
       "      <td>715800</td>\n",
       "      <td>944100</td>\n",
       "      <td>24966600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-22</th>\n",
       "      <td>26.40</td>\n",
       "      <td>35.78</td>\n",
       "      <td>11.78</td>\n",
       "      <td>31.30</td>\n",
       "      <td>91.24</td>\n",
       "      <td>26.40</td>\n",
       "      <td>35.78</td>\n",
       "      <td>11.78</td>\n",
       "      <td>31.30</td>\n",
       "      <td>95.35</td>\n",
       "      <td>...</td>\n",
       "      <td>26.50</td>\n",
       "      <td>34.70</td>\n",
       "      <td>12.06</td>\n",
       "      <td>31.49</td>\n",
       "      <td>96.50</td>\n",
       "      <td>2309800.0</td>\n",
       "      <td>22345200</td>\n",
       "      <td>1378000</td>\n",
       "      <td>3328600</td>\n",
       "      <td>50160600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-23</th>\n",
       "      <td>26.90</td>\n",
       "      <td>35.62</td>\n",
       "      <td>12.26</td>\n",
       "      <td>31.32</td>\n",
       "      <td>92.77</td>\n",
       "      <td>26.90</td>\n",
       "      <td>35.62</td>\n",
       "      <td>12.26</td>\n",
       "      <td>31.32</td>\n",
       "      <td>96.95</td>\n",
       "      <td>...</td>\n",
       "      <td>26.70</td>\n",
       "      <td>36.55</td>\n",
       "      <td>11.99</td>\n",
       "      <td>31.41</td>\n",
       "      <td>96.59</td>\n",
       "      <td>2017200.0</td>\n",
       "      <td>30320600</td>\n",
       "      <td>1031800</td>\n",
       "      <td>3134300</td>\n",
       "      <td>35756200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-24</th>\n",
       "      <td>29.24</td>\n",
       "      <td>37.15</td>\n",
       "      <td>12.20</td>\n",
       "      <td>31.43</td>\n",
       "      <td>93.71</td>\n",
       "      <td>29.24</td>\n",
       "      <td>37.15</td>\n",
       "      <td>12.20</td>\n",
       "      <td>31.43</td>\n",
       "      <td>97.93</td>\n",
       "      <td>...</td>\n",
       "      <td>27.30</td>\n",
       "      <td>35.91</td>\n",
       "      <td>12.22</td>\n",
       "      <td>31.45</td>\n",
       "      <td>97.13</td>\n",
       "      <td>3524300.0</td>\n",
       "      <td>17988200</td>\n",
       "      <td>575600</td>\n",
       "      <td>1481300</td>\n",
       "      <td>21856100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-25</th>\n",
       "      <td>26.77</td>\n",
       "      <td>34.75</td>\n",
       "      <td>11.74</td>\n",
       "      <td>30.82</td>\n",
       "      <td>91.58</td>\n",
       "      <td>26.77</td>\n",
       "      <td>34.75</td>\n",
       "      <td>11.74</td>\n",
       "      <td>30.82</td>\n",
       "      <td>95.71</td>\n",
       "      <td>...</td>\n",
       "      <td>29.74</td>\n",
       "      <td>37.24</td>\n",
       "      <td>12.28</td>\n",
       "      <td>31.40</td>\n",
       "      <td>98.70</td>\n",
       "      <td>2629700.0</td>\n",
       "      <td>18396600</td>\n",
       "      <td>913000</td>\n",
       "      <td>1917900</td>\n",
       "      <td>24471000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-26</th>\n",
       "      <td>28.20</td>\n",
       "      <td>32.87</td>\n",
       "      <td>11.21</td>\n",
       "      <td>30.76</td>\n",
       "      <td>90.44</td>\n",
       "      <td>28.20</td>\n",
       "      <td>32.87</td>\n",
       "      <td>11.21</td>\n",
       "      <td>30.76</td>\n",
       "      <td>94.52</td>\n",
       "      <td>...</td>\n",
       "      <td>27.37</td>\n",
       "      <td>34.87</td>\n",
       "      <td>11.91</td>\n",
       "      <td>30.86</td>\n",
       "      <td>96.55</td>\n",
       "      <td>4897300.0</td>\n",
       "      <td>23030500</td>\n",
       "      <td>1528000</td>\n",
       "      <td>2332800</td>\n",
       "      <td>42856000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-01</th>\n",
       "      <td>28.59</td>\n",
       "      <td>33.97</td>\n",
       "      <td>10.89</td>\n",
       "      <td>30.41</td>\n",
       "      <td>94.32</td>\n",
       "      <td>28.59</td>\n",
       "      <td>33.97</td>\n",
       "      <td>10.89</td>\n",
       "      <td>30.41</td>\n",
       "      <td>98.57</td>\n",
       "      <td>...</td>\n",
       "      <td>29.30</td>\n",
       "      <td>33.49</td>\n",
       "      <td>11.38</td>\n",
       "      <td>30.93</td>\n",
       "      <td>96.00</td>\n",
       "      <td>1903500.0</td>\n",
       "      <td>13912900</td>\n",
       "      <td>1453400</td>\n",
       "      <td>2442600</td>\n",
       "      <td>32798000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-02</th>\n",
       "      <td>27.82</td>\n",
       "      <td>34.84</td>\n",
       "      <td>12.18</td>\n",
       "      <td>30.48</td>\n",
       "      <td>97.22</td>\n",
       "      <td>27.82</td>\n",
       "      <td>34.84</td>\n",
       "      <td>12.18</td>\n",
       "      <td>30.48</td>\n",
       "      <td>101.60</td>\n",
       "      <td>...</td>\n",
       "      <td>28.34</td>\n",
       "      <td>33.30</td>\n",
       "      <td>10.80</td>\n",
       "      <td>30.19</td>\n",
       "      <td>97.50</td>\n",
       "      <td>1537200.0</td>\n",
       "      <td>14488600</td>\n",
       "      <td>3012500</td>\n",
       "      <td>2929900</td>\n",
       "      <td>47565800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-03</th>\n",
       "      <td>28.30</td>\n",
       "      <td>35.42</td>\n",
       "      <td>14.14</td>\n",
       "      <td>30.50</td>\n",
       "      <td>96.02</td>\n",
       "      <td>28.30</td>\n",
       "      <td>35.42</td>\n",
       "      <td>14.14</td>\n",
       "      <td>30.50</td>\n",
       "      <td>100.35</td>\n",
       "      <td>...</td>\n",
       "      <td>27.63</td>\n",
       "      <td>35.05</td>\n",
       "      <td>13.01</td>\n",
       "      <td>30.33</td>\n",
       "      <td>102.00</td>\n",
       "      <td>3634100.0</td>\n",
       "      <td>25212200</td>\n",
       "      <td>6427500</td>\n",
       "      <td>3009500</td>\n",
       "      <td>41473300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-04</th>\n",
       "      <td>27.04</td>\n",
       "      <td>35.21</td>\n",
       "      <td>13.39</td>\n",
       "      <td>32.37</td>\n",
       "      <td>94.60</td>\n",
       "      <td>27.04</td>\n",
       "      <td>35.21</td>\n",
       "      <td>13.39</td>\n",
       "      <td>32.37</td>\n",
       "      <td>98.86</td>\n",
       "      <td>...</td>\n",
       "      <td>28.52</td>\n",
       "      <td>35.20</td>\n",
       "      <td>14.27</td>\n",
       "      <td>31.43</td>\n",
       "      <td>99.40</td>\n",
       "      <td>2996400.0</td>\n",
       "      <td>23150100</td>\n",
       "      <td>4100900</td>\n",
       "      <td>4348500</td>\n",
       "      <td>48492500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-05</th>\n",
       "      <td>26.36</td>\n",
       "      <td>37.00</td>\n",
       "      <td>13.76</td>\n",
       "      <td>32.33</td>\n",
       "      <td>100.21</td>\n",
       "      <td>26.36</td>\n",
       "      <td>37.00</td>\n",
       "      <td>13.76</td>\n",
       "      <td>32.33</td>\n",
       "      <td>100.21</td>\n",
       "      <td>...</td>\n",
       "      <td>27.04</td>\n",
       "      <td>35.21</td>\n",
       "      <td>13.50</td>\n",
       "      <td>32.80</td>\n",
       "      <td>94.72</td>\n",
       "      <td>2946100.0</td>\n",
       "      <td>20146600</td>\n",
       "      <td>3374600</td>\n",
       "      <td>2835900</td>\n",
       "      <td>46503300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-08</th>\n",
       "      <td>22.86</td>\n",
       "      <td>36.50</td>\n",
       "      <td>12.93</td>\n",
       "      <td>31.72</td>\n",
       "      <td>99.67</td>\n",
       "      <td>22.86</td>\n",
       "      <td>36.50</td>\n",
       "      <td>12.93</td>\n",
       "      <td>31.72</td>\n",
       "      <td>99.67</td>\n",
       "      <td>...</td>\n",
       "      <td>25.50</td>\n",
       "      <td>36.62</td>\n",
       "      <td>13.60</td>\n",
       "      <td>32.08</td>\n",
       "      <td>99.20</td>\n",
       "      <td>4109500.0</td>\n",
       "      <td>16757200</td>\n",
       "      <td>2358800</td>\n",
       "      <td>2364700</td>\n",
       "      <td>39677300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-09</th>\n",
       "      <td>22.88</td>\n",
       "      <td>35.16</td>\n",
       "      <td>13.60</td>\n",
       "      <td>32.84</td>\n",
       "      <td>98.67</td>\n",
       "      <td>22.88</td>\n",
       "      <td>35.16</td>\n",
       "      <td>13.60</td>\n",
       "      <td>32.84</td>\n",
       "      <td>98.67</td>\n",
       "      <td>...</td>\n",
       "      <td>23.23</td>\n",
       "      <td>35.49</td>\n",
       "      <td>13.06</td>\n",
       "      <td>31.90</td>\n",
       "      <td>97.50</td>\n",
       "      <td>1909700.0</td>\n",
       "      <td>22505000</td>\n",
       "      <td>1790900</td>\n",
       "      <td>3185400</td>\n",
       "      <td>40537000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-10</th>\n",
       "      <td>23.76</td>\n",
       "      <td>34.15</td>\n",
       "      <td>14.52</td>\n",
       "      <td>33.21</td>\n",
       "      <td>97.15</td>\n",
       "      <td>23.76</td>\n",
       "      <td>34.15</td>\n",
       "      <td>14.52</td>\n",
       "      <td>33.21</td>\n",
       "      <td>97.15</td>\n",
       "      <td>...</td>\n",
       "      <td>23.21</td>\n",
       "      <td>34.96</td>\n",
       "      <td>13.98</td>\n",
       "      <td>32.92</td>\n",
       "      <td>97.50</td>\n",
       "      <td>2359900.0</td>\n",
       "      <td>16178900</td>\n",
       "      <td>5401000</td>\n",
       "      <td>3207600</td>\n",
       "      <td>31311800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-11</th>\n",
       "      <td>24.40</td>\n",
       "      <td>37.28</td>\n",
       "      <td>14.75</td>\n",
       "      <td>33.14</td>\n",
       "      <td>99.70</td>\n",
       "      <td>24.40</td>\n",
       "      <td>37.28</td>\n",
       "      <td>14.75</td>\n",
       "      <td>33.14</td>\n",
       "      <td>99.70</td>\n",
       "      <td>...</td>\n",
       "      <td>24.27</td>\n",
       "      <td>34.80</td>\n",
       "      <td>14.59</td>\n",
       "      <td>33.20</td>\n",
       "      <td>98.99</td>\n",
       "      <td>1579000.0</td>\n",
       "      <td>28810900</td>\n",
       "      <td>2412000</td>\n",
       "      <td>2209400</td>\n",
       "      <td>26203200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-12</th>\n",
       "      <td>25.18</td>\n",
       "      <td>37.62</td>\n",
       "      <td>15.95</td>\n",
       "      <td>33.04</td>\n",
       "      <td>97.40</td>\n",
       "      <td>25.18</td>\n",
       "      <td>37.62</td>\n",
       "      <td>15.95</td>\n",
       "      <td>33.04</td>\n",
       "      <td>97.40</td>\n",
       "      <td>...</td>\n",
       "      <td>24.19</td>\n",
       "      <td>36.69</td>\n",
       "      <td>14.44</td>\n",
       "      <td>33.00</td>\n",
       "      <td>99.00</td>\n",
       "      <td>1489300.0</td>\n",
       "      <td>14528400</td>\n",
       "      <td>4605800</td>\n",
       "      <td>2284600</td>\n",
       "      <td>21115500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-15</th>\n",
       "      <td>24.76</td>\n",
       "      <td>35.83</td>\n",
       "      <td>17.05</td>\n",
       "      <td>33.80</td>\n",
       "      <td>96.82</td>\n",
       "      <td>24.76</td>\n",
       "      <td>35.83</td>\n",
       "      <td>17.05</td>\n",
       "      <td>33.80</td>\n",
       "      <td>96.82</td>\n",
       "      <td>...</td>\n",
       "      <td>24.97</td>\n",
       "      <td>37.37</td>\n",
       "      <td>15.80</td>\n",
       "      <td>33.00</td>\n",
       "      <td>96.50</td>\n",
       "      <td>1525600.0</td>\n",
       "      <td>18438700</td>\n",
       "      <td>4097000</td>\n",
       "      <td>3294000</td>\n",
       "      <td>20059000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-16</th>\n",
       "      <td>26.15</td>\n",
       "      <td>36.95</td>\n",
       "      <td>17.30</td>\n",
       "      <td>34.32</td>\n",
       "      <td>96.51</td>\n",
       "      <td>26.15</td>\n",
       "      <td>36.95</td>\n",
       "      <td>17.30</td>\n",
       "      <td>34.32</td>\n",
       "      <td>96.51</td>\n",
       "      <td>...</td>\n",
       "      <td>24.79</td>\n",
       "      <td>36.52</td>\n",
       "      <td>17.05</td>\n",
       "      <td>33.82</td>\n",
       "      <td>97.04</td>\n",
       "      <td>1694500.0</td>\n",
       "      <td>15645800</td>\n",
       "      <td>4654800</td>\n",
       "      <td>2798200</td>\n",
       "      <td>19174300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-17</th>\n",
       "      <td>25.51</td>\n",
       "      <td>37.64</td>\n",
       "      <td>18.89</td>\n",
       "      <td>35.69</td>\n",
       "      <td>97.90</td>\n",
       "      <td>25.51</td>\n",
       "      <td>37.64</td>\n",
       "      <td>18.89</td>\n",
       "      <td>35.69</td>\n",
       "      <td>97.90</td>\n",
       "      <td>...</td>\n",
       "      <td>26.05</td>\n",
       "      <td>37.11</td>\n",
       "      <td>17.25</td>\n",
       "      <td>34.50</td>\n",
       "      <td>96.40</td>\n",
       "      <td>1467200.0</td>\n",
       "      <td>11492600</td>\n",
       "      <td>4060400</td>\n",
       "      <td>4975800</td>\n",
       "      <td>21424300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-18</th>\n",
       "      <td>23.89</td>\n",
       "      <td>37.04</td>\n",
       "      <td>19.57</td>\n",
       "      <td>35.16</td>\n",
       "      <td>96.16</td>\n",
       "      <td>23.89</td>\n",
       "      <td>37.04</td>\n",
       "      <td>19.57</td>\n",
       "      <td>35.16</td>\n",
       "      <td>96.16</td>\n",
       "      <td>...</td>\n",
       "      <td>25.46</td>\n",
       "      <td>37.36</td>\n",
       "      <td>18.65</td>\n",
       "      <td>35.55</td>\n",
       "      <td>97.70</td>\n",
       "      <td>1251900.0</td>\n",
       "      <td>14294700</td>\n",
       "      <td>5309800</td>\n",
       "      <td>2290600</td>\n",
       "      <td>19156100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-19</th>\n",
       "      <td>23.85</td>\n",
       "      <td>35.61</td>\n",
       "      <td>19.26</td>\n",
       "      <td>35.84</td>\n",
       "      <td>94.78</td>\n",
       "      <td>23.85</td>\n",
       "      <td>35.61</td>\n",
       "      <td>19.26</td>\n",
       "      <td>35.84</td>\n",
       "      <td>94.78</td>\n",
       "      <td>...</td>\n",
       "      <td>24.04</td>\n",
       "      <td>37.18</td>\n",
       "      <td>19.73</td>\n",
       "      <td>35.16</td>\n",
       "      <td>96.10</td>\n",
       "      <td>1325400.0</td>\n",
       "      <td>16650600</td>\n",
       "      <td>3054500</td>\n",
       "      <td>2146000</td>\n",
       "      <td>38643000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-22</th>\n",
       "      <td>24.01</td>\n",
       "      <td>35.00</td>\n",
       "      <td>17.00</td>\n",
       "      <td>35.80</td>\n",
       "      <td>93.21</td>\n",
       "      <td>24.01</td>\n",
       "      <td>35.00</td>\n",
       "      <td>17.00</td>\n",
       "      <td>35.80</td>\n",
       "      <td>93.21</td>\n",
       "      <td>...</td>\n",
       "      <td>23.85</td>\n",
       "      <td>34.95</td>\n",
       "      <td>18.90</td>\n",
       "      <td>35.91</td>\n",
       "      <td>93.52</td>\n",
       "      <td>799500.0</td>\n",
       "      <td>15154300</td>\n",
       "      <td>5352100</td>\n",
       "      <td>2723400</td>\n",
       "      <td>21120800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-23</th>\n",
       "      <td>23.88</td>\n",
       "      <td>33.50</td>\n",
       "      <td>17.80</td>\n",
       "      <td>36.13</td>\n",
       "      <td>91.06</td>\n",
       "      <td>23.88</td>\n",
       "      <td>33.50</td>\n",
       "      <td>17.80</td>\n",
       "      <td>36.13</td>\n",
       "      <td>91.06</td>\n",
       "      <td>...</td>\n",
       "      <td>23.88</td>\n",
       "      <td>35.17</td>\n",
       "      <td>16.44</td>\n",
       "      <td>35.88</td>\n",
       "      <td>93.34</td>\n",
       "      <td>493000.0</td>\n",
       "      <td>13755900</td>\n",
       "      <td>5191100</td>\n",
       "      <td>2363300</td>\n",
       "      <td>20518500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-24</th>\n",
       "      <td>22.70</td>\n",
       "      <td>33.30</td>\n",
       "      <td>18.75</td>\n",
       "      <td>35.73</td>\n",
       "      <td>93.15</td>\n",
       "      <td>22.70</td>\n",
       "      <td>33.30</td>\n",
       "      <td>18.75</td>\n",
       "      <td>35.73</td>\n",
       "      <td>93.15</td>\n",
       "      <td>...</td>\n",
       "      <td>23.97</td>\n",
       "      <td>34.09</td>\n",
       "      <td>18.02</td>\n",
       "      <td>36.19</td>\n",
       "      <td>92.00</td>\n",
       "      <td>805100.0</td>\n",
       "      <td>16377400</td>\n",
       "      <td>4042600</td>\n",
       "      <td>2254700</td>\n",
       "      <td>24726000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-25</th>\n",
       "      <td>22.40</td>\n",
       "      <td>33.47</td>\n",
       "      <td>18.17</td>\n",
       "      <td>35.78</td>\n",
       "      <td>92.44</td>\n",
       "      <td>22.40</td>\n",
       "      <td>33.47</td>\n",
       "      <td>18.17</td>\n",
       "      <td>35.78</td>\n",
       "      <td>92.44</td>\n",
       "      <td>...</td>\n",
       "      <td>22.76</td>\n",
       "      <td>33.62</td>\n",
       "      <td>18.56</td>\n",
       "      <td>35.70</td>\n",
       "      <td>93.04</td>\n",
       "      <td>1274500.0</td>\n",
       "      <td>17808000</td>\n",
       "      <td>3810300</td>\n",
       "      <td>2390500</td>\n",
       "      <td>23644400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-26</th>\n",
       "      <td>23.02</td>\n",
       "      <td>35.14</td>\n",
       "      <td>18.50</td>\n",
       "      <td>36.10</td>\n",
       "      <td>95.53</td>\n",
       "      <td>23.02</td>\n",
       "      <td>35.14</td>\n",
       "      <td>18.50</td>\n",
       "      <td>36.10</td>\n",
       "      <td>95.53</td>\n",
       "      <td>...</td>\n",
       "      <td>22.80</td>\n",
       "      <td>34.12</td>\n",
       "      <td>17.47</td>\n",
       "      <td>35.78</td>\n",
       "      <td>93.74</td>\n",
       "      <td>1141700.0</td>\n",
       "      <td>16394400</td>\n",
       "      <td>4990800</td>\n",
       "      <td>1618600</td>\n",
       "      <td>23056100</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>244 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Adj Close                                         Close           \\\n",
       "            CASH3.SA CSNA3.SA ETER3.SA TAEE11.SA VALE3.SA CASH3.SA CSNA3.SA   \n",
       "Date                                                                          \n",
       "2020-03-30       NaN     7.05     2.64     22.72    38.37      NaN     7.06   \n",
       "2020-03-31       NaN     6.97     2.40     23.12    39.70      NaN     6.98   \n",
       "2020-04-01       NaN     6.83     2.41     22.84    39.83      NaN     6.84   \n",
       "2020-04-02       NaN     6.96     2.19     23.69    39.29      NaN     6.97   \n",
       "2020-04-03       NaN     6.24     2.20     23.82    37.20      NaN     6.25   \n",
       "2020-04-06       NaN     6.54     2.31     24.36    39.61      NaN     6.55   \n",
       "2020-04-07       NaN     6.94     2.34     24.27    40.21      NaN     6.95   \n",
       "2020-04-08       NaN     7.39     2.40     24.31    39.96      NaN     7.41   \n",
       "2020-04-09       NaN     7.16     2.48     24.18    39.75      NaN     7.17   \n",
       "2020-04-13       NaN     7.31     2.46     24.27    40.94      NaN     7.33   \n",
       "2020-04-14       NaN     7.42     2.76     24.72    40.90      NaN     7.44   \n",
       "2020-04-15       NaN     7.27     2.75     24.65    39.67      NaN     7.29   \n",
       "2020-04-16       NaN     7.42     2.59     24.28    39.27      NaN     7.44   \n",
       "2020-04-17       NaN     7.57     2.64     24.07    40.41      NaN     7.59   \n",
       "2020-04-20       NaN     7.30     2.63     24.14    39.00      NaN     7.32   \n",
       "2020-04-22       NaN     7.32     2.79     24.89    39.40      NaN     7.34   \n",
       "2020-04-23       NaN     7.48     2.69     25.15    39.96      NaN     7.50   \n",
       "2020-04-24       NaN     7.07     2.48     24.44    40.19      NaN     7.08   \n",
       "2020-04-27       NaN     7.23     2.68     25.28    40.92      NaN     7.25   \n",
       "2020-04-28       NaN     7.79     2.70     25.44    40.97      NaN     7.81   \n",
       "2020-04-29       NaN     9.01     2.74     24.90    42.92      NaN     9.03   \n",
       "2020-04-30       NaN     8.94     2.63     24.72    41.20      NaN     8.96   \n",
       "2020-05-04       NaN     8.22     2.63     24.63    40.35      NaN     8.23   \n",
       "2020-05-05       NaN     7.95     2.62     24.86    40.14      NaN     7.96   \n",
       "2020-05-06       NaN     8.09     2.65     24.81    40.72      NaN     8.10   \n",
       "2020-05-07       NaN     8.49     2.63     24.29    42.30      NaN     8.49   \n",
       "2020-05-08       NaN     8.51     2.59     24.47    44.87      NaN     8.51   \n",
       "2020-05-11       NaN     8.02     2.53     24.07    43.84      NaN     8.02   \n",
       "2020-05-12       NaN     7.88     2.45     23.84    43.59      NaN     7.88   \n",
       "2020-05-13       NaN     7.52     2.48     24.00    44.58      NaN     7.52   \n",
       "...              ...      ...      ...       ...      ...      ...      ...   \n",
       "2021-02-10     29.71    34.39    12.86     32.55    90.62    29.71    34.39   \n",
       "2021-02-11     28.58    33.02    12.69     32.51    89.09    28.58    33.02   \n",
       "2021-02-12     28.30    32.83    12.55     32.43    89.84    28.30    32.83   \n",
       "2021-02-18     27.66    34.16    12.10     31.96    93.20    27.66    34.16   \n",
       "2021-02-19     27.74    35.26    12.23     32.02    93.55    27.74    35.26   \n",
       "2021-02-22     26.40    35.78    11.78     31.30    91.24    26.40    35.78   \n",
       "2021-02-23     26.90    35.62    12.26     31.32    92.77    26.90    35.62   \n",
       "2021-02-24     29.24    37.15    12.20     31.43    93.71    29.24    37.15   \n",
       "2021-02-25     26.77    34.75    11.74     30.82    91.58    26.77    34.75   \n",
       "2021-02-26     28.20    32.87    11.21     30.76    90.44    28.20    32.87   \n",
       "2021-03-01     28.59    33.97    10.89     30.41    94.32    28.59    33.97   \n",
       "2021-03-02     27.82    34.84    12.18     30.48    97.22    27.82    34.84   \n",
       "2021-03-03     28.30    35.42    14.14     30.50    96.02    28.30    35.42   \n",
       "2021-03-04     27.04    35.21    13.39     32.37    94.60    27.04    35.21   \n",
       "2021-03-05     26.36    37.00    13.76     32.33   100.21    26.36    37.00   \n",
       "2021-03-08     22.86    36.50    12.93     31.72    99.67    22.86    36.50   \n",
       "2021-03-09     22.88    35.16    13.60     32.84    98.67    22.88    35.16   \n",
       "2021-03-10     23.76    34.15    14.52     33.21    97.15    23.76    34.15   \n",
       "2021-03-11     24.40    37.28    14.75     33.14    99.70    24.40    37.28   \n",
       "2021-03-12     25.18    37.62    15.95     33.04    97.40    25.18    37.62   \n",
       "2021-03-15     24.76    35.83    17.05     33.80    96.82    24.76    35.83   \n",
       "2021-03-16     26.15    36.95    17.30     34.32    96.51    26.15    36.95   \n",
       "2021-03-17     25.51    37.64    18.89     35.69    97.90    25.51    37.64   \n",
       "2021-03-18     23.89    37.04    19.57     35.16    96.16    23.89    37.04   \n",
       "2021-03-19     23.85    35.61    19.26     35.84    94.78    23.85    35.61   \n",
       "2021-03-22     24.01    35.00    17.00     35.80    93.21    24.01    35.00   \n",
       "2021-03-23     23.88    33.50    17.80     36.13    91.06    23.88    33.50   \n",
       "2021-03-24     22.70    33.30    18.75     35.73    93.15    22.70    33.30   \n",
       "2021-03-25     22.40    33.47    18.17     35.78    92.44    22.40    33.47   \n",
       "2021-03-26     23.02    35.14    18.50     36.10    95.53    23.02    35.14   \n",
       "\n",
       "                                        ...     Open                    \\\n",
       "           ETER3.SA TAEE11.SA VALE3.SA  ... CASH3.SA CSNA3.SA ETER3.SA   \n",
       "Date                                    ...                              \n",
       "2020-03-30     2.64     25.27    41.77  ...      NaN     6.84     2.83   \n",
       "2020-03-31     2.40     25.72    43.22  ...      NaN     7.06     2.69   \n",
       "2020-04-01     2.41     25.41    43.37  ...      NaN     6.63     2.30   \n",
       "2020-04-02     2.19     26.35    42.78  ...      NaN     6.98     2.53   \n",
       "2020-04-03     2.20     26.50    40.50  ...      NaN     7.00     2.19   \n",
       "2020-04-06     2.31     27.10    43.13  ...      NaN     6.68     2.30   \n",
       "2020-04-07     2.34     27.00    43.78  ...      NaN     6.92     2.43   \n",
       "2020-04-08     2.40     27.04    43.51  ...      NaN     7.00     2.34   \n",
       "2020-04-09     2.48     26.90    43.28  ...      NaN     7.60     2.43   \n",
       "2020-04-13     2.46     27.00    44.57  ...      NaN     7.10     2.49   \n",
       "2020-04-14     2.76     27.50    44.53  ...      NaN     7.52     2.48   \n",
       "2020-04-15     2.75     27.42    43.19  ...      NaN     7.20     2.64   \n",
       "2020-04-16     2.59     27.01    42.76  ...      NaN     7.43     2.81   \n",
       "2020-04-17     2.64     26.78    44.00  ...      NaN     7.55     2.72   \n",
       "2020-04-20     2.63     26.85    42.46  ...      NaN     7.37     2.64   \n",
       "2020-04-22     2.79     27.69    42.90  ...      NaN     7.35     2.61   \n",
       "2020-04-23     2.69     27.98    43.51  ...      NaN     7.35     2.75   \n",
       "2020-04-24     2.48     27.19    43.76  ...      NaN     7.39     2.63   \n",
       "2020-04-27     2.68     28.12    44.55  ...      NaN     7.26     2.52   \n",
       "2020-04-28     2.70     28.30    44.61  ...      NaN     7.50     2.78   \n",
       "2020-04-29     2.74     27.70    46.73  ...      NaN     8.06     2.77   \n",
       "2020-04-30     2.63     27.50    44.86  ...      NaN     8.65     2.67   \n",
       "2020-05-04     2.63     27.40    43.93  ...      NaN     8.58     2.53   \n",
       "2020-05-05     2.62     27.65    43.70  ...      NaN     8.40     2.73   \n",
       "2020-05-06     2.65     27.60    44.33  ...      NaN     8.02     2.78   \n",
       "2020-05-07     2.63     26.85    46.05  ...      NaN     8.26     2.67   \n",
       "2020-05-08     2.59     27.05    48.85  ...      NaN     8.74     2.65   \n",
       "2020-05-11     2.53     26.60    47.73  ...      NaN     8.40     2.52   \n",
       "2020-05-12     2.45     26.35    47.46  ...      NaN     8.15     2.53   \n",
       "2020-05-13     2.48     26.53    48.54  ...      NaN     8.01     2.43   \n",
       "...             ...       ...      ...  ...      ...      ...      ...   \n",
       "2021-02-10    12.86     32.55    94.70  ...    31.52    35.95    13.38   \n",
       "2021-02-11    12.69     32.51    93.10  ...    29.71    34.83    12.86   \n",
       "2021-02-12    12.55     32.43    93.89  ...    28.58    32.81    12.70   \n",
       "2021-02-18    12.10     31.96    97.40  ...    28.89    34.81    12.60   \n",
       "2021-02-19    12.23     32.02    97.77  ...    27.66    34.17    12.10   \n",
       "2021-02-22    11.78     31.30    95.35  ...    26.50    34.70    12.06   \n",
       "2021-02-23    12.26     31.32    96.95  ...    26.70    36.55    11.99   \n",
       "2021-02-24    12.20     31.43    97.93  ...    27.30    35.91    12.22   \n",
       "2021-02-25    11.74     30.82    95.71  ...    29.74    37.24    12.28   \n",
       "2021-02-26    11.21     30.76    94.52  ...    27.37    34.87    11.91   \n",
       "2021-03-01    10.89     30.41    98.57  ...    29.30    33.49    11.38   \n",
       "2021-03-02    12.18     30.48   101.60  ...    28.34    33.30    10.80   \n",
       "2021-03-03    14.14     30.50   100.35  ...    27.63    35.05    13.01   \n",
       "2021-03-04    13.39     32.37    98.86  ...    28.52    35.20    14.27   \n",
       "2021-03-05    13.76     32.33   100.21  ...    27.04    35.21    13.50   \n",
       "2021-03-08    12.93     31.72    99.67  ...    25.50    36.62    13.60   \n",
       "2021-03-09    13.60     32.84    98.67  ...    23.23    35.49    13.06   \n",
       "2021-03-10    14.52     33.21    97.15  ...    23.21    34.96    13.98   \n",
       "2021-03-11    14.75     33.14    99.70  ...    24.27    34.80    14.59   \n",
       "2021-03-12    15.95     33.04    97.40  ...    24.19    36.69    14.44   \n",
       "2021-03-15    17.05     33.80    96.82  ...    24.97    37.37    15.80   \n",
       "2021-03-16    17.30     34.32    96.51  ...    24.79    36.52    17.05   \n",
       "2021-03-17    18.89     35.69    97.90  ...    26.05    37.11    17.25   \n",
       "2021-03-18    19.57     35.16    96.16  ...    25.46    37.36    18.65   \n",
       "2021-03-19    19.26     35.84    94.78  ...    24.04    37.18    19.73   \n",
       "2021-03-22    17.00     35.80    93.21  ...    23.85    34.95    18.90   \n",
       "2021-03-23    17.80     36.13    91.06  ...    23.88    35.17    16.44   \n",
       "2021-03-24    18.75     35.73    93.15  ...    23.97    34.09    18.02   \n",
       "2021-03-25    18.17     35.78    92.44  ...    22.76    33.62    18.56   \n",
       "2021-03-26    18.50     36.10    95.53  ...    22.80    34.12    17.47   \n",
       "\n",
       "                                  Volume                               \\\n",
       "           TAEE11.SA VALE3.SA   CASH3.SA  CSNA3.SA ETER3.SA TAEE11.SA   \n",
       "Date                                                                    \n",
       "2020-03-30     25.66    40.92        NaN  14322900  1542099   1948800   \n",
       "2020-03-31     25.30    42.30        NaN  16501900  1161587   2426100   \n",
       "2020-04-01     25.28    41.81        NaN   9417800   433835   2706500   \n",
       "2020-04-02     25.51    43.95        NaN  11170000   815841   3710300   \n",
       "2020-04-03     26.50    42.80        NaN  16042700   975703   5383600   \n",
       "2020-04-06     27.00    42.60        NaN  10198800   371234   2765800   \n",
       "2020-04-07     28.12    45.19        NaN  16963600   430209   3160500   \n",
       "2020-04-08     27.01    43.50        NaN  11954800   358970   3120200   \n",
       "2020-04-09     27.22    43.95        NaN  10845800   577274   2474200   \n",
       "2020-04-13     26.77    43.20        NaN  11763100   238993   1859700   \n",
       "2020-04-14     27.45    45.62        NaN   9863100  1024333   2289600   \n",
       "2020-04-15     27.29    43.50        NaN  10329200  1039477   2208000   \n",
       "2020-04-16     27.62    43.80        NaN  12883000   582819   1809200   \n",
       "2020-04-17     27.32    43.90        NaN  11465300   415492   3419300   \n",
       "2020-04-20     26.54    43.26        NaN   8522900   274933   2422300   \n",
       "2020-04-22     26.66    42.60        NaN   7547100   839729   2434500   \n",
       "2020-04-23     27.80    43.29        NaN  18280500  1009083   2425100   \n",
       "2020-04-24     27.55    43.37        NaN  20463400   581433   5022000   \n",
       "2020-04-27     27.19    44.46        NaN  13778300   605642   3256900   \n",
       "2020-04-28     28.56    45.20        NaN  19016300   459323   2261100   \n",
       "2020-04-29     28.44    45.35        NaN  34574500   628250   3182600   \n",
       "2020-04-30     27.35    45.71        NaN  25377300   367288   3868100   \n",
       "2020-05-04     27.11    43.70        NaN  17770600   323563   3169900   \n",
       "2020-05-05     27.52    44.45        NaN  13641300   338600   2035400   \n",
       "2020-05-06     27.80    44.19        NaN  12166400   289400   1745700   \n",
       "2020-05-07     27.49    45.63        NaN  22482600   206100   3163500   \n",
       "2020-05-08     27.23    47.50        NaN  14286000   298400   2131500   \n",
       "2020-05-11     27.00    48.21        NaN  11776700   201300   1981100   \n",
       "2020-05-12     26.75    48.43        NaN  11590800   231900   2555200   \n",
       "2020-05-13     26.31    48.17        NaN  12905000   184400   2359300   \n",
       "...              ...      ...        ...       ...      ...       ...   \n",
       "2021-02-10     32.88    94.66  4369200.0  17540700  1102000   1682300   \n",
       "2021-02-11     32.88    95.47  2634600.0  17174200   900200   1222900   \n",
       "2021-02-12     32.51    93.12  3521000.0  19754000   757500    936000   \n",
       "2021-02-18     32.25    97.36  3036200.0  29101500   708300   1789600   \n",
       "2021-02-19     31.94    97.21  2009700.0  15722600   715800    944100   \n",
       "2021-02-22     31.49    96.50  2309800.0  22345200  1378000   3328600   \n",
       "2021-02-23     31.41    96.59  2017200.0  30320600  1031800   3134300   \n",
       "2021-02-24     31.45    97.13  3524300.0  17988200   575600   1481300   \n",
       "2021-02-25     31.40    98.70  2629700.0  18396600   913000   1917900   \n",
       "2021-02-26     30.86    96.55  4897300.0  23030500  1528000   2332800   \n",
       "2021-03-01     30.93    96.00  1903500.0  13912900  1453400   2442600   \n",
       "2021-03-02     30.19    97.50  1537200.0  14488600  3012500   2929900   \n",
       "2021-03-03     30.33   102.00  3634100.0  25212200  6427500   3009500   \n",
       "2021-03-04     31.43    99.40  2996400.0  23150100  4100900   4348500   \n",
       "2021-03-05     32.80    94.72  2946100.0  20146600  3374600   2835900   \n",
       "2021-03-08     32.08    99.20  4109500.0  16757200  2358800   2364700   \n",
       "2021-03-09     31.90    97.50  1909700.0  22505000  1790900   3185400   \n",
       "2021-03-10     32.92    97.50  2359900.0  16178900  5401000   3207600   \n",
       "2021-03-11     33.20    98.99  1579000.0  28810900  2412000   2209400   \n",
       "2021-03-12     33.00    99.00  1489300.0  14528400  4605800   2284600   \n",
       "2021-03-15     33.00    96.50  1525600.0  18438700  4097000   3294000   \n",
       "2021-03-16     33.82    97.04  1694500.0  15645800  4654800   2798200   \n",
       "2021-03-17     34.50    96.40  1467200.0  11492600  4060400   4975800   \n",
       "2021-03-18     35.55    97.70  1251900.0  14294700  5309800   2290600   \n",
       "2021-03-19     35.16    96.10  1325400.0  16650600  3054500   2146000   \n",
       "2021-03-22     35.91    93.52   799500.0  15154300  5352100   2723400   \n",
       "2021-03-23     35.88    93.34   493000.0  13755900  5191100   2363300   \n",
       "2021-03-24     36.19    92.00   805100.0  16377400  4042600   2254700   \n",
       "2021-03-25     35.70    93.04  1274500.0  17808000  3810300   2390500   \n",
       "2021-03-26     35.78    93.74  1141700.0  16394400  4990800   1618600   \n",
       "\n",
       "                      \n",
       "            VALE3.SA  \n",
       "Date                  \n",
       "2020-03-30  31298300  \n",
       "2020-03-31  39238000  \n",
       "2020-04-01  37092100  \n",
       "2020-04-02  34372600  \n",
       "2020-04-03  31650000  \n",
       "2020-04-06  32019300  \n",
       "2020-04-07  34191900  \n",
       "2020-04-08  29464500  \n",
       "2020-04-09  29827800  \n",
       "2020-04-13  22066800  \n",
       "2020-04-14  24713600  \n",
       "2020-04-15  28808700  \n",
       "2020-04-16  24442900  \n",
       "2020-04-17  23604600  \n",
       "2020-04-20  29050700  \n",
       "2020-04-22  22693600  \n",
       "2020-04-23  27171100  \n",
       "2020-04-24  55165900  \n",
       "2020-04-27  25580600  \n",
       "2020-04-28  25680000  \n",
       "2020-04-29  33207500  \n",
       "2020-04-30  25720300  \n",
       "2020-05-04  16994300  \n",
       "2020-05-05  19070600  \n",
       "2020-05-06  26602700  \n",
       "2020-05-07  42194300  \n",
       "2020-05-08  33922800  \n",
       "2020-05-11  24783100  \n",
       "2020-05-12  21806900  \n",
       "2020-05-13  34159500  \n",
       "...              ...  \n",
       "2021-02-10  40318300  \n",
       "2021-02-11  19775900  \n",
       "2021-02-12  14760700  \n",
       "2021-02-18  33088500  \n",
       "2021-02-19  24966600  \n",
       "2021-02-22  50160600  \n",
       "2021-02-23  35756200  \n",
       "2021-02-24  21856100  \n",
       "2021-02-25  24471000  \n",
       "2021-02-26  42856000  \n",
       "2021-03-01  32798000  \n",
       "2021-03-02  47565800  \n",
       "2021-03-03  41473300  \n",
       "2021-03-04  48492500  \n",
       "2021-03-05  46503300  \n",
       "2021-03-08  39677300  \n",
       "2021-03-09  40537000  \n",
       "2021-03-10  31311800  \n",
       "2021-03-11  26203200  \n",
       "2021-03-12  21115500  \n",
       "2021-03-15  20059000  \n",
       "2021-03-16  19174300  \n",
       "2021-03-17  21424300  \n",
       "2021-03-18  19156100  \n",
       "2021-03-19  38643000  \n",
       "2021-03-22  21120800  \n",
       "2021-03-23  20518500  \n",
       "2021-03-24  24726000  \n",
       "2021-03-25  23644400  \n",
       "2021-03-26  23056100  \n",
       "\n",
       "[244 rows x 30 columns]"
      ]
     },
     "execution_count": 406,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stocks_all = download(rb)\n",
    "stocks_all"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 407,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Insira um multiplicador para a modelagem: \n"
     ]
    }
   ],
   "source": [
    "import random\n",
    "\n",
    "# Markowits\n",
    "print(\"Insira um multiplicador para a modelagem: \")\n",
    "multiplicador = 10\n",
    "n_days = len(stocks_all)\n",
    "stocks = stocks_all['Adj Close']\n",
    "log_ret = np.log(stocks / stocks.shift(1))\n",
    "\n",
    "# Admite que a mesma sequencia randomica\n",
    "np.random.seed(42)\n",
    "num_ports = multiplicador * 500 * len(stocks.columns)\n",
    "all_weights = np.zeros((num_ports, len(stocks.columns)))\n",
    "ret_arr = np.zeros(num_ports)\n",
    "vol_arr = np.zeros(num_ports)\n",
    "sharpe_arr = np.zeros(num_ports)\n",
    "\n",
    "for x in range(num_ports):\n",
    "    # Weights\n",
    "    weights = np.array(np.random.random(len(stocks.columns)))\n",
    "    weights = weights/np.sum(weights)\n",
    "\n",
    "    # Save weights\n",
    "    all_weights[x,:] = weights\n",
    "\n",
    "    # Expected return\n",
    "    ret_arr[x] = np.sum( (log_ret.mean() * weights * n_days))\n",
    "\n",
    "    # Expected volatility\n",
    "    vol_arr[x] = np.sqrt(np.dot(weights.T, np.dot(log_ret.cov() * n_days, weights)))\n",
    "\n",
    "    # Sharpe Ratio\n",
    "    sharpe_arr[x] = ret_arr[x]/vol_arr[x]\n",
    "\n",
    "# Para operar na venda utilize o agrmin()\n",
    "\n",
    "maximo = sharpe_arr.argmax()\n",
    "# maximo = sharpe_arr.argmin()\n",
    "\n",
    "# maximo = vol_arr.argmax()\n",
    "# maximo = vol_arr.argmin()\n",
    "\n",
    "         \n",
    "max_sr_ret = ret_arr[maximo]\n",
    "max_sr_vol = vol_arr[maximo]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 408,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,8))\n",
    "plt.scatter(vol_arr, ret_arr, c=sharpe_arr, cmap='viridis')\n",
    "plt.colorbar(label='Grau do Indice Sharpe ')\n",
    "plt.xlabel('Risco')\n",
    "plt.ylabel('Retorno')\n",
    "plt.scatter(max_sr_vol, max_sr_ret,c='red', s=200) # red dot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 409,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Expectativa de retorno diário:   0.642 %\n"
     ]
    }
   ],
   "source": [
    "# Fator expectativa\n",
    "exp = (max_sr_ret - max_sr_vol)/(max_sr_ret + max_sr_vol)\n",
    "expec_real = 1 +(exp/100)\n",
    "# exp = expec_real**252d\n",
    "\n",
    "print(\"Expectativa de retorno diário:   %.3f\" % exp + \" %\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 410,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Reg_price</th>\n",
       "      <th>Coef_price</th>\n",
       "      <th>Reg_int</th>\n",
       "      <th>Coef_int</th>\n",
       "      <th>Rel_price_ret</th>\n",
       "      <th>Pct_up_day</th>\n",
       "      <th>Pct_up_month</th>\n",
       "      <th>Sharpe</th>\n",
       "      <th>Base_price</th>\n",
       "      <th>Target_buy</th>\n",
       "      <th>Target_sell</th>\n",
       "      <th>Actual_price</th>\n",
       "      <th>Ret_real</th>\n",
       "      <th>Stop_loss</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>VALE3.SA</th>\n",
       "      <td>34.3509</td>\n",
       "      <td>0.246963</td>\n",
       "      <td>0.00451735</td>\n",
       "      <td>-4.29071e-06</td>\n",
       "      <td>-57557.6</td>\n",
       "      <td>52.2634</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.12992</td>\n",
       "      <td>34.3508</td>\n",
       "      <td>82.4238</td>\n",
       "      <td>105.41</td>\n",
       "      <td>95.53</td>\n",
       "      <td>148.971</td>\n",
       "      <td>-32.0209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CASH3.SA</th>\n",
       "      <td>-8.2134</td>\n",
       "      <td>0.130715</td>\n",
       "      <td>-0.00161885</td>\n",
       "      <td>4.90518e-05</td>\n",
       "      <td>2664.84</td>\n",
       "      <td>57.7778</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.56425</td>\n",
       "      <td>-8.21381</td>\n",
       "      <td>22.0925</td>\n",
       "      <td>25.1265</td>\n",
       "      <td>23.02</td>\n",
       "      <td>142.571</td>\n",
       "      <td>-67.8406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ETER3.SA</th>\n",
       "      <td>0.254335</td>\n",
       "      <td>0.0650928</td>\n",
       "      <td>0.00764294</td>\n",
       "      <td>1.3956e-05</td>\n",
       "      <td>4664.16</td>\n",
       "      <td>56.7901</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.761962</td>\n",
       "      <td>0.254338</td>\n",
       "      <td>17.5491</td>\n",
       "      <td>18.7239</td>\n",
       "      <td>18.5</td>\n",
       "      <td>600.758</td>\n",
       "      <td>-49.3126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CSNA3.SA</th>\n",
       "      <td>2.94603</td>\n",
       "      <td>0.137135</td>\n",
       "      <td>0.00954577</td>\n",
       "      <td>-1.80908e-05</td>\n",
       "      <td>-7580.39</td>\n",
       "      <td>53.9095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.874876</td>\n",
       "      <td>2.94598</td>\n",
       "      <td>32.3784</td>\n",
       "      <td>37.0516</td>\n",
       "      <td>35.14</td>\n",
       "      <td>398.44</td>\n",
       "      <td>-45.8082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TAEE11.SA</th>\n",
       "      <td>23.3692</td>\n",
       "      <td>0.0439585</td>\n",
       "      <td>0.00183502</td>\n",
       "      <td>1.17652e-06</td>\n",
       "      <td>37363</td>\n",
       "      <td>51.8519</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.808982</td>\n",
       "      <td>23.3692</td>\n",
       "      <td>34.8822</td>\n",
       "      <td>36.4608</td>\n",
       "      <td>36.1</td>\n",
       "      <td>58.8908</td>\n",
       "      <td>-17.6327</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Reg_price Coef_price     Reg_int     Coef_int Rel_price_ret  \\\n",
       "VALE3.SA    34.3509   0.246963  0.00451735 -4.29071e-06      -57557.6   \n",
       "CASH3.SA    -8.2134   0.130715 -0.00161885  4.90518e-05       2664.84   \n",
       "ETER3.SA   0.254335  0.0650928  0.00764294   1.3956e-05       4664.16   \n",
       "CSNA3.SA    2.94603   0.137135  0.00954577 -1.80908e-05      -7580.39   \n",
       "TAEE11.SA   23.3692  0.0439585  0.00183502  1.17652e-06         37363   \n",
       "\n",
       "          Pct_up_day Pct_up_month    Sharpe Base_price Target_buy Target_sell  \\\n",
       "VALE3.SA     52.2634          NaN   1.12992    34.3508    82.4238      105.41   \n",
       "CASH3.SA     57.7778          NaN   1.56425   -8.21381    22.0925     25.1265   \n",
       "ETER3.SA     56.7901          NaN  0.761962   0.254338    17.5491     18.7239   \n",
       "CSNA3.SA     53.9095          NaN  0.874876    2.94598    32.3784     37.0516   \n",
       "TAEE11.SA    51.8519          NaN  0.808982    23.3692    34.8822     36.4608   \n",
       "\n",
       "          Actual_price Ret_real Stop_loss  \n",
       "VALE3.SA         95.53  148.971  -32.0209  \n",
       "CASH3.SA         23.02  142.571  -67.8406  \n",
       "ETER3.SA          18.5  600.758  -49.3126  \n",
       "CSNA3.SA         35.14   398.44  -45.8082  \n",
       "TAEE11.SA         36.1  58.8908  -17.6327  "
      ]
     },
     "execution_count": 410,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "finals_stocks.loc[rb]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 411,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "##==================CASH3.SA==================##\n",
      "\n",
      "Proporcao no portifolio          :    10.30%\n",
      "\n",
      "Numero de papeis a comprar       :        45\n",
      "Valor proporcional               : R$ 1030.42\n",
      "\n",
      "Preço atual                      : R$ 23.02\n",
      "\n",
      "##==================CSNA3.SA==================##\n",
      "\n",
      "Proporcao no portifolio          :    12.87%\n",
      "\n",
      "Numero de papeis a comprar       :        37\n",
      "Valor proporcional               : R$ 1287.01\n",
      "\n",
      "Preço atual                      : R$ 35.14\n",
      "\n",
      "##==================ETER3.SA==================##\n",
      "\n",
      "Proporcao no portifolio          :    10.88%\n",
      "\n",
      "Numero de papeis a comprar       :        59\n",
      "Valor proporcional               : R$ 1088.27\n",
      "\n",
      "Preço atual                      : R$ 18.50\n",
      "\n",
      "##==================TAEE11.SA==================##\n",
      "\n",
      "Proporcao no portifolio          :    45.51%\n",
      "\n",
      "Numero de papeis a comprar       :        126\n",
      "Valor proporcional               : R$ 4550.56\n",
      "\n",
      "Preço atual                      : R$ 36.10\n",
      "\n",
      "##==================VALE3.SA==================##\n",
      "\n",
      "Proporcao no portifolio          :    20.44%\n",
      "\n",
      "Numero de papeis a comprar       :        21\n",
      "Valor proporcional               : R$ 2043.74\n",
      "\n",
      "Preço atual                      : R$ 95.53\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "# Simulacao de compra\n",
    "money = 10000\n",
    "risk = 100\n",
    "last_price = stocks[-1:].iloc[0]\n",
    "\n",
    "# Pesos na carteira\n",
    "df = pd.DataFrame(index=stocks.columns, columns = ['Pesos','Valor_investido'])\n",
    "df['Pesos'] = all_weights[maximo]\n",
    "                    \n",
    "                    # ou rb\n",
    "for i in range(len(stocks.columns)):\n",
    "    stocks_qtd = money * all_weights[maximo][i]\n",
    "    stocks_qtd = stocks_qtd / last_price[i]\n",
    "    risk_calc = abs(risk/(finals_stocks['Stop_loss'][i])*100)\n",
    "    prop_value = stocks_qtd*last_price[i]\n",
    "    df['Valor_investido'][i] = prop_value\n",
    "    profit_tx =  finals_stocks['Target_sell'].loc[stocks.columns[i]] / finals_stocks['Actual_price'].loc[stocks.columns[i]]\n",
    "    profit_tx = (profit_tx-1)*100\n",
    "    \n",
    "    \n",
    "    \n",
    "    print(\"##==================\"+stocks.iloc[i].index[i]+\"==================##\")\n",
    "    print()\n",
    "    print(\"Proporcao no portifolio          :    %.2f\" %(all_weights[maximo][i]*100) +\"%\")\n",
    "    print()\n",
    "    print(\"Numero de papeis a comprar       :        %.0f\" % stocks_qtd)\n",
    "    print(\"Valor proporcional               : R$ %.2f\" % prop_value)\n",
    "    print()\n",
    "    print(\"Preço atual                      : R$ %.2f\" % finals_stocks['Actual_price'].loc[stocks.columns[i]])\n",
    "    print()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 348,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pesos</th>\n",
       "      <th>Valor_investido</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CASH3.SA</th>\n",
       "      <td>0.143498</td>\n",
       "      <td>1434.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LWSA3.SA</th>\n",
       "      <td>0.148857</td>\n",
       "      <td>1488.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SUZB3.SA</th>\n",
       "      <td>0.169404</td>\n",
       "      <td>1694.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TASA4.SA</th>\n",
       "      <td>0.209892</td>\n",
       "      <td>2098.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VALE3.SA</th>\n",
       "      <td>0.328349</td>\n",
       "      <td>3283.49</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "             Pesos Valor_investido\n",
       "CASH3.SA  0.143498         1434.98\n",
       "LWSA3.SA  0.148857         1488.57\n",
       "SUZB3.SA  0.169404         1694.04\n",
       "TASA4.SA  0.209892         2098.92\n",
       "VALE3.SA  0.328349         3283.49"
      ]
     },
     "execution_count": 348,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Backtest</h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 364,
   "metadata": {},
   "outputs": [],
   "source": [
    "E_Day = 28\n",
    "E_Month = 3\n",
    "E_Year = 2021\n",
    "S_Day = 21\n",
    "S_Month = 3\n",
    "S_Year = 2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 365,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  5 of 5 downloaded\n"
     ]
    },
    {
     "data": {
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       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"5\" halign=\"left\">Adj Close</th>\n",
       "      <th colspan=\"5\" halign=\"left\">Close</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"5\" halign=\"left\">Open</th>\n",
       "      <th colspan=\"5\" halign=\"left\">Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>CASH3.SA</th>\n",
       "      <th>LWSA3.SA</th>\n",
       "      <th>SUZB3.SA</th>\n",
       "      <th>TASA4.SA</th>\n",
       "      <th>VALE3.SA</th>\n",
       "      <th>CASH3.SA</th>\n",
       "      <th>LWSA3.SA</th>\n",
       "      <th>SUZB3.SA</th>\n",
       "      <th>TASA4.SA</th>\n",
       "      <th>VALE3.SA</th>\n",
       "      <th>...</th>\n",
       "      <th>CASH3.SA</th>\n",
       "      <th>LWSA3.SA</th>\n",
       "      <th>SUZB3.SA</th>\n",
       "      <th>TASA4.SA</th>\n",
       "      <th>VALE3.SA</th>\n",
       "      <th>CASH3.SA</th>\n",
       "      <th>LWSA3.SA</th>\n",
       "      <th>SUZB3.SA</th>\n",
       "      <th>TASA4.SA</th>\n",
       "      <th>VALE3.SA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-03-22</th>\n",
       "      <td>24.01</td>\n",
       "      <td>24.81</td>\n",
       "      <td>72.41</td>\n",
       "      <td>22.88</td>\n",
       "      <td>93.21</td>\n",
       "      <td>24.01</td>\n",
       "      <td>24.81</td>\n",
       "      <td>72.41</td>\n",
       "      <td>22.88</td>\n",
       "      <td>93.21</td>\n",
       "      <td>...</td>\n",
       "      <td>23.85</td>\n",
       "      <td>24.22</td>\n",
       "      <td>73.20</td>\n",
       "      <td>23.67</td>\n",
       "      <td>93.52</td>\n",
       "      <td>799500</td>\n",
       "      <td>5612800</td>\n",
       "      <td>5230200</td>\n",
       "      <td>4910800</td>\n",
       "      <td>21120800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-23</th>\n",
       "      <td>23.88</td>\n",
       "      <td>24.74</td>\n",
       "      <td>71.77</td>\n",
       "      <td>23.60</td>\n",
       "      <td>91.06</td>\n",
       "      <td>23.88</td>\n",
       "      <td>24.74</td>\n",
       "      <td>71.77</td>\n",
       "      <td>23.60</td>\n",
       "      <td>91.06</td>\n",
       "      <td>...</td>\n",
       "      <td>23.88</td>\n",
       "      <td>24.80</td>\n",
       "      <td>72.15</td>\n",
       "      <td>22.98</td>\n",
       "      <td>93.34</td>\n",
       "      <td>493000</td>\n",
       "      <td>8578000</td>\n",
       "      <td>5040500</td>\n",
       "      <td>3630800</td>\n",
       "      <td>20518500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-24</th>\n",
       "      <td>22.70</td>\n",
       "      <td>24.10</td>\n",
       "      <td>73.66</td>\n",
       "      <td>22.74</td>\n",
       "      <td>93.15</td>\n",
       "      <td>22.70</td>\n",
       "      <td>24.10</td>\n",
       "      <td>73.66</td>\n",
       "      <td>22.74</td>\n",
       "      <td>93.15</td>\n",
       "      <td>...</td>\n",
       "      <td>23.97</td>\n",
       "      <td>24.95</td>\n",
       "      <td>73.25</td>\n",
       "      <td>23.60</td>\n",
       "      <td>92.00</td>\n",
       "      <td>805100</td>\n",
       "      <td>6012200</td>\n",
       "      <td>9830500</td>\n",
       "      <td>3277200</td>\n",
       "      <td>24726000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-25</th>\n",
       "      <td>22.40</td>\n",
       "      <td>23.50</td>\n",
       "      <td>73.20</td>\n",
       "      <td>22.87</td>\n",
       "      <td>92.44</td>\n",
       "      <td>22.40</td>\n",
       "      <td>23.50</td>\n",
       "      <td>73.20</td>\n",
       "      <td>22.87</td>\n",
       "      <td>92.44</td>\n",
       "      <td>...</td>\n",
       "      <td>22.76</td>\n",
       "      <td>23.46</td>\n",
       "      <td>74.51</td>\n",
       "      <td>22.90</td>\n",
       "      <td>93.04</td>\n",
       "      <td>1274500</td>\n",
       "      <td>8156200</td>\n",
       "      <td>8424900</td>\n",
       "      <td>2138000</td>\n",
       "      <td>23644400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-26</th>\n",
       "      <td>23.02</td>\n",
       "      <td>23.00</td>\n",
       "      <td>72.50</td>\n",
       "      <td>22.72</td>\n",
       "      <td>95.53</td>\n",
       "      <td>23.02</td>\n",
       "      <td>23.00</td>\n",
       "      <td>72.50</td>\n",
       "      <td>22.72</td>\n",
       "      <td>95.53</td>\n",
       "      <td>...</td>\n",
       "      <td>22.80</td>\n",
       "      <td>23.64</td>\n",
       "      <td>73.26</td>\n",
       "      <td>23.05</td>\n",
       "      <td>93.74</td>\n",
       "      <td>1141700</td>\n",
       "      <td>8629700</td>\n",
       "      <td>5120100</td>\n",
       "      <td>1443600</td>\n",
       "      <td>23056100</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Adj Close                                        Close           \\\n",
       "            CASH3.SA LWSA3.SA SUZB3.SA TASA4.SA VALE3.SA CASH3.SA LWSA3.SA   \n",
       "Date                                                                         \n",
       "2021-03-22     24.01    24.81    72.41    22.88    93.21    24.01    24.81   \n",
       "2021-03-23     23.88    24.74    71.77    23.60    91.06    23.88    24.74   \n",
       "2021-03-24     22.70    24.10    73.66    22.74    93.15    22.70    24.10   \n",
       "2021-03-25     22.40    23.50    73.20    22.87    92.44    22.40    23.50   \n",
       "2021-03-26     23.02    23.00    72.50    22.72    95.53    23.02    23.00   \n",
       "\n",
       "                                       ...     Open                    \\\n",
       "           SUZB3.SA TASA4.SA VALE3.SA  ... CASH3.SA LWSA3.SA SUZB3.SA   \n",
       "Date                                   ...                              \n",
       "2021-03-22    72.41    22.88    93.21  ...    23.85    24.22    73.20   \n",
       "2021-03-23    71.77    23.60    91.06  ...    23.88    24.80    72.15   \n",
       "2021-03-24    73.66    22.74    93.15  ...    23.97    24.95    73.25   \n",
       "2021-03-25    73.20    22.87    92.44  ...    22.76    23.46    74.51   \n",
       "2021-03-26    72.50    22.72    95.53  ...    22.80    23.64    73.26   \n",
       "\n",
       "                               Volume                                       \n",
       "           TASA4.SA VALE3.SA CASH3.SA LWSA3.SA SUZB3.SA TASA4.SA  VALE3.SA  \n",
       "Date                                                                        \n",
       "2021-03-22    23.67    93.52   799500  5612800  5230200  4910800  21120800  \n",
       "2021-03-23    22.98    93.34   493000  8578000  5040500  3630800  20518500  \n",
       "2021-03-24    23.60    92.00   805100  6012200  9830500  3277200  24726000  \n",
       "2021-03-25    22.90    93.04  1274500  8156200  8424900  2138000  23644400  \n",
       "2021-03-26    23.05    93.74  1141700  8629700  5120100  1443600  23056100  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 365,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    ## Analise dos ativos com maior volume  \n",
    "best_names = list(df.index[:])\n",
    "stocks_all=yahoo(best_names,S_Day, S_Month, S_Year, E_Day, E_Month, E_Year)    \n",
    "stocks_close = stocks_all['Adj Close']\n",
    "stocks_all.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 368,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Expectativa de retorno médio diário :   0.675 %\n",
      "Retorno real médio diário           :   -0.137 %\n",
      "\n",
      "Taxa de erro da previsão            :   -1.204 %\n"
     ]
    }
   ],
   "source": [
    "# Fator expectativa por normalização de risco e retorno\n",
    "\n",
    "exp = (max_sr_ret - max_sr_vol)/(max_sr_ret + max_sr_vol)\n",
    "print(\"Expectativa de retorno médio diário :   %.3f\" % exp + \" %\")\n",
    "\n",
    "# Retorno médio dos ativos somados\n",
    "\n",
    "retorno = stocks_close.diff().dropna().mean().sum()\n",
    "print(\"Retorno real médio diário           :   %.3f\" % retorno + \" %\")\n",
    "\n",
    "# Cálculo do erro de previsão\n",
    "\n",
    "erro = (retorno - exp)/exp\n",
    "print()\n",
    "print(\"Taxa de erro da previsão            :   %.3f\" % erro + \" %\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 369,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CASH3.SA    0.958767\n",
       "LWSA3.SA    0.927046\n",
       "SUZB3.SA    1.001243\n",
       "TASA4.SA    0.993007\n",
       "VALE3.SA    1.024890\n",
       "dtype: float64"
      ]
     },
     "execution_count": 369,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "retorno_real = stocks_close.iloc[-1] / stocks_close.iloc[0]\n",
    "retorno_real"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 370,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pesos</th>\n",
       "      <th>Valor_investido</th>\n",
       "      <th>Retorno_real</th>\n",
       "      <th>Montante_final</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CASH3.SA</th>\n",
       "      <td>0.143498</td>\n",
       "      <td>1434.98</td>\n",
       "      <td>0.958767</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LWSA3.SA</th>\n",
       "      <td>0.148857</td>\n",
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       "      <td>0.927046</td>\n",
       "      <td>13479.2</td>\n",
       "    </tr>\n",
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       "      <th>SUZB3.SA</th>\n",
       "      <td>0.169404</td>\n",
       "      <td>1694.04</td>\n",
       "      <td>1.001243</td>\n",
       "      <td>4264.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TASA4.SA</th>\n",
       "      <td>0.209892</td>\n",
       "      <td>2098.92</td>\n",
       "      <td>0.993007</td>\n",
       "      <td>20643.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VALE3.SA</th>\n",
       "      <td>0.328349</td>\n",
       "      <td>3283.49</td>\n",
       "      <td>1.024890</td>\n",
       "      <td>10015.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Pesos Valor_investido  Retorno_real Montante_final\n",
       "CASH3.SA  0.143498         1434.98      0.958767            NaN\n",
       "LWSA3.SA  0.148857         1488.57      0.927046        13479.2\n",
       "SUZB3.SA  0.169404         1694.04      1.001243        4264.52\n",
       "TASA4.SA  0.209892         2098.92      0.993007        20643.9\n",
       "VALE3.SA  0.328349         3283.49      1.024890        10015.1"
      ]
     },
     "execution_count": 370,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Retorno_real'] = retorno_real\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 371,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9901.388283580458"
      ]
     },
     "execution_count": 371,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Montante_final'] = df['Valor_investido'] * df['Retorno_real']\n",
    "df['Montante_final'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 372,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Previsão de lucro acumulado         : R$ 10337.38\n",
      "\n",
      "Previsão de retorno acumulado       : 3.37 %\n",
      "\n",
      "Montante real acumulado             : R$ 9901.39\n",
      "\n",
      "Retorno real                        : -0.99 %\n",
      "\n",
      "Taxa de desempenho                  : -4.22 %\n"
     ]
    }
   ],
   "source": [
    "# Comparação do desempenho \n",
    "# Previsto\n",
    "fator_multiplicador = ((len(stocks_close) * exp)/100)+1\n",
    "port_predict = money * fator_multiplicador\n",
    "exp_port_predict = (port_predict/money)-1\n",
    "montante_real = df['Montante_final'].sum()\n",
    "\n",
    "print(\"Previsão de lucro acumulado         : R$ %.2f\" % port_predict)\n",
    "print()\n",
    "print(\"Previsão de retorno acumulado       : %.2f\" % (exp_port_predict*100)+\" %\")\n",
    "print()\n",
    "print(\"Montante real acumulado             : R$ %.2f\" % montante_real)\n",
    "print()\n",
    "print(\"Retorno real                        : %.2f\" % (((montante_real-money)/money)*100)+\" %\")\n",
    "print()\n",
    "print(\"Taxa de desempenho                  : %.2f\" % ((float((montante_real-port_predict)/port_predict))*100)+\" %\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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