fb-prophet-stock-prediction-v1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Using Facebook Prophet model to predict HK stock price\n",
    "\n",
    "Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well.\n",
    "\n",
    "https://facebook.github.io/prophet/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import necessary libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from fbprophet import Prophet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-02-28</td>\n",
       "      <td>76.300003</td>\n",
       "      <td>76.900002</td>\n",
       "      <td>75.900002</td>\n",
       "      <td>76.900002</td>\n",
       "      <td>75.507645</td>\n",
       "      <td>41504793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-03-02</td>\n",
       "      <td>77.000000</td>\n",
       "      <td>77.550003</td>\n",
       "      <td>76.300003</td>\n",
       "      <td>76.449997</td>\n",
       "      <td>75.065788</td>\n",
       "      <td>31230325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-03-03</td>\n",
       "      <td>76.500000</td>\n",
       "      <td>77.250000</td>\n",
       "      <td>75.300003</td>\n",
       "      <td>75.500000</td>\n",
       "      <td>74.132988</td>\n",
       "      <td>31135827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-03-04</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>74.900002</td>\n",
       "      <td>75.050003</td>\n",
       "      <td>73.691139</td>\n",
       "      <td>29495534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-03-05</td>\n",
       "      <td>76.699997</td>\n",
       "      <td>77.650002</td>\n",
       "      <td>75.750000</td>\n",
       "      <td>77.650002</td>\n",
       "      <td>76.244064</td>\n",
       "      <td>36107180</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date       Open       High        Low      Close  Adj Close    Volume\n",
       "0  2020-02-28  76.300003  76.900002  75.900002  76.900002  75.507645  41504793\n",
       "1  2020-03-02  77.000000  77.550003  76.300003  76.449997  75.065788  31230325\n",
       "2  2020-03-03  76.500000  77.250000  75.300003  75.500000  74.132988  31135827\n",
       "3  2020-03-04  76.000000  76.000000  74.900002  75.050003  73.691139  29495534\n",
       "4  2020-03-05  76.699997  77.650002  75.750000  77.650002  76.244064  36107180"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load dataset (past 6 months data)\n",
    "data = pd.read_csv(\"./stock_data/1299.HK.6months.csv\") \n",
    "data.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>247.000000</td>\n",
       "      <td>247.000000</td>\n",
       "      <td>247.000000</td>\n",
       "      <td>247.000000</td>\n",
       "      <td>247.000000</td>\n",
       "      <td>2.470000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>80.292713</td>\n",
       "      <td>81.040688</td>\n",
       "      <td>78.942510</td>\n",
       "      <td>79.958097</td>\n",
       "      <td>79.544371</td>\n",
       "      <td>2.741304e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>11.338782</td>\n",
       "      <td>11.398077</td>\n",
       "      <td>11.111253</td>\n",
       "      <td>11.333094</td>\n",
       "      <td>11.687667</td>\n",
       "      <td>1.334581e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>61.099998</td>\n",
       "      <td>63.099998</td>\n",
       "      <td>60.049999</td>\n",
       "      <td>60.700001</td>\n",
       "      <td>59.600964</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>72.000000</td>\n",
       "      <td>72.525002</td>\n",
       "      <td>70.575001</td>\n",
       "      <td>71.700001</td>\n",
       "      <td>70.763550</td>\n",
       "      <td>1.871740e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>76.699997</td>\n",
       "      <td>77.900002</td>\n",
       "      <td>75.800003</td>\n",
       "      <td>76.650002</td>\n",
       "      <td>76.400002</td>\n",
       "      <td>2.410256e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>88.974998</td>\n",
       "      <td>89.575001</td>\n",
       "      <td>87.550003</td>\n",
       "      <td>88.250000</td>\n",
       "      <td>88.250000</td>\n",
       "      <td>3.284126e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>108.400002</td>\n",
       "      <td>109.300003</td>\n",
       "      <td>104.500000</td>\n",
       "      <td>108.900002</td>\n",
       "      <td>108.900002</td>\n",
       "      <td>8.448093e+07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Open        High         Low       Close   Adj Close  \\\n",
       "count  247.000000  247.000000  247.000000  247.000000  247.000000   \n",
       "mean    80.292713   81.040688   78.942510   79.958097   79.544371   \n",
       "std     11.338782   11.398077   11.111253   11.333094   11.687667   \n",
       "min     61.099998   63.099998   60.049999   60.700001   59.600964   \n",
       "25%     72.000000   72.525002   70.575001   71.700001   70.763550   \n",
       "50%     76.699997   77.900002   75.800003   76.650002   76.400002   \n",
       "75%     88.974998   89.575001   87.550003   88.250000   88.250000   \n",
       "max    108.400002  109.300003  104.500000  108.900002  108.900002   \n",
       "\n",
       "             Volume  \n",
       "count  2.470000e+02  \n",
       "mean   2.741304e+07  \n",
       "std    1.334581e+07  \n",
       "min    0.000000e+00  \n",
       "25%    1.871740e+07  \n",
       "50%    2.410256e+07  \n",
       "75%    3.284126e+07  \n",
       "max    8.448093e+07  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Describe dataset\n",
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>ds</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-02-28</td>\n",
       "      <td>76.900002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-03-02</td>\n",
       "      <td>76.449997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-03-03</td>\n",
       "      <td>75.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-03-04</td>\n",
       "      <td>75.050003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-03-05</td>\n",
       "      <td>77.650002</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           ds          y\n",
       "0  2020-02-28  76.900002\n",
       "1  2020-03-02  76.449997\n",
       "2  2020-03-03  75.500000\n",
       "3  2020-03-04  75.050003\n",
       "4  2020-03-05  77.650002"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select date and price features from dataset\n",
    "data = data[[\"Date\", \"Close\"]]\n",
    "# Rename the features for the model fitting\n",
    "data = data.rename(columns = {\"Date\":\"ds\", \"Close\":\"y\"})\n",
    "data.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:numexpr.utils:NumExpr defaulting to 4 threads.\n",
      "INFO:fbprophet:Disabling yearly seasonality. Run prophet with yearly_seasonality=True to override this.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<fbprophet.forecaster.Prophet at 0x7f85ca84d9a0>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fit the model using all data (past 6 months data)\n",
    "m = Prophet(daily_seasonality = True)\n",
    "m.fit(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the model with next 30 days forcast\n",
    "future = m.make_future_dataframe(periods=30)\n",
    "prediction = m.predict(future)\n",
    "m.plot(prediction)\n",
    "plt.title(\"Prediction of the AIA Group Limited (1299.HK) Stock Price using the Prophet\")\n",
    "plt.xlabel(\"Date\")\n",
    "plt.ylabel(\"Close Stock Price\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-11-30</td>\n",
       "      <td>88.500000</td>\n",
       "      <td>89.150002</td>\n",
       "      <td>84.949997</td>\n",
       "      <td>84.949997</td>\n",
       "      <td>84.949997</td>\n",
       "      <td>35518927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-12-01</td>\n",
       "      <td>86.750000</td>\n",
       "      <td>88.349998</td>\n",
       "      <td>86.349998</td>\n",
       "      <td>88.199997</td>\n",
       "      <td>88.199997</td>\n",
       "      <td>26930347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-12-02</td>\n",
       "      <td>88.349998</td>\n",
       "      <td>88.599998</td>\n",
       "      <td>87.000000</td>\n",
       "      <td>88.300003</td>\n",
       "      <td>88.300003</td>\n",
       "      <td>20086955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-12-03</td>\n",
       "      <td>88.750000</td>\n",
       "      <td>89.000000</td>\n",
       "      <td>87.550003</td>\n",
       "      <td>88.900002</td>\n",
       "      <td>88.900002</td>\n",
       "      <td>17287337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-12-04</td>\n",
       "      <td>88.699997</td>\n",
       "      <td>89.050003</td>\n",
       "      <td>87.550003</td>\n",
       "      <td>89.000000</td>\n",
       "      <td>89.000000</td>\n",
       "      <td>21877325</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date       Open       High        Low      Close  Adj Close    Volume\n",
       "0  2020-11-30  88.500000  89.150002  84.949997  84.949997  84.949997  35518927\n",
       "1  2020-12-01  86.750000  88.349998  86.349998  88.199997  88.199997  26930347\n",
       "2  2020-12-02  88.349998  88.599998  87.000000  88.300003  88.300003  20086955\n",
       "3  2020-12-03  88.750000  89.000000  87.550003  88.900002  88.900002  17287337\n",
       "4  2020-12-04  88.699997  89.050003  87.550003  89.000000  89.000000  21877325"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load dataset (past 3 months data)\n",
    "data2 = pd.read_csv(\"./stock_data/1299.HK.3months.csv\") \n",
    "data2.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>61.000000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>6.100000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>96.982787</td>\n",
       "      <td>97.935246</td>\n",
       "      <td>95.354099</td>\n",
       "      <td>96.759017</td>\n",
       "      <td>96.759017</td>\n",
       "      <td>2.229489e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>5.982362</td>\n",
       "      <td>6.189665</td>\n",
       "      <td>5.756513</td>\n",
       "      <td>6.040361</td>\n",
       "      <td>6.040361</td>\n",
       "      <td>8.523874e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>86.750000</td>\n",
       "      <td>87.550003</td>\n",
       "      <td>84.949997</td>\n",
       "      <td>84.949997</td>\n",
       "      <td>84.949997</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>91.150002</td>\n",
       "      <td>91.150002</td>\n",
       "      <td>89.250000</td>\n",
       "      <td>90.250000</td>\n",
       "      <td>90.250000</td>\n",
       "      <td>1.741182e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>97.500000</td>\n",
       "      <td>98.750000</td>\n",
       "      <td>96.199997</td>\n",
       "      <td>97.750000</td>\n",
       "      <td>97.750000</td>\n",
       "      <td>2.265087e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>102.000000</td>\n",
       "      <td>103.000000</td>\n",
       "      <td>100.099998</td>\n",
       "      <td>101.400002</td>\n",
       "      <td>101.400002</td>\n",
       "      <td>2.716702e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>108.400002</td>\n",
       "      <td>109.300003</td>\n",
       "      <td>104.500000</td>\n",
       "      <td>108.900002</td>\n",
       "      <td>108.900002</td>\n",
       "      <td>4.195539e+07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Open        High         Low       Close   Adj Close  \\\n",
       "count   61.000000   61.000000   61.000000   61.000000   61.000000   \n",
       "mean    96.982787   97.935246   95.354099   96.759017   96.759017   \n",
       "std      5.982362    6.189665    5.756513    6.040361    6.040361   \n",
       "min     86.750000   87.550003   84.949997   84.949997   84.949997   \n",
       "25%     91.150002   91.150002   89.250000   90.250000   90.250000   \n",
       "50%     97.500000   98.750000   96.199997   97.750000   97.750000   \n",
       "75%    102.000000  103.000000  100.099998  101.400002  101.400002   \n",
       "max    108.400002  109.300003  104.500000  108.900002  108.900002   \n",
       "\n",
       "             Volume  \n",
       "count  6.100000e+01  \n",
       "mean   2.229489e+07  \n",
       "std    8.523874e+06  \n",
       "min    0.000000e+00  \n",
       "25%    1.741182e+07  \n",
       "50%    2.265087e+07  \n",
       "75%    2.716702e+07  \n",
       "max    4.195539e+07  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Describe dataset\n",
    "data2.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>ds</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-11-30</td>\n",
       "      <td>84.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-12-01</td>\n",
       "      <td>88.199997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-12-02</td>\n",
       "      <td>88.300003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-12-03</td>\n",
       "      <td>88.900002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-12-04</td>\n",
       "      <td>89.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           ds          y\n",
       "0  2020-11-30  84.949997\n",
       "1  2020-12-01  88.199997\n",
       "2  2020-12-02  88.300003\n",
       "3  2020-12-03  88.900002\n",
       "4  2020-12-04  89.000000"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select date and price features from dataset\n",
    "data2 = data2[[\"Date\", \"Close\"]]\n",
    "# Rename the features for the model fitting\n",
    "data2 = data2.rename(columns = {\"Date\":\"ds\", \"Close\":\"y\"})\n",
    "data2.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:fbprophet:Disabling yearly seasonality. Run prophet with yearly_seasonality=True to override this.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<fbprophet.forecaster.Prophet at 0x7f85cc4c91c0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fit the model using all data (past 3 months data)\n",
    "m2 = Prophet(daily_seasonality = True)\n",
    "m2.fit(data2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the model with next 30 days forcast\n",
    "future = m2.make_future_dataframe(periods=30)\n",
    "prediction = m2.predict(future)\n",
    "m2.plot(prediction)\n",
    "plt.title(\"Prediction of the AIA Group Limited (1299.HK) Stock Price using the Prophet\")\n",
    "plt.xlabel(\"Date\")\n",
    "plt.ylabel(\"Close Stock Price\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-02-03</td>\n",
       "      <td>77.699997</td>\n",
       "      <td>79.199997</td>\n",
       "      <td>77.050003</td>\n",
       "      <td>78.500000</td>\n",
       "      <td>77.078674</td>\n",
       "      <td>35847965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-02-04</td>\n",
       "      <td>80.550003</td>\n",
       "      <td>80.550003</td>\n",
       "      <td>78.849998</td>\n",
       "      <td>79.250000</td>\n",
       "      <td>77.815086</td>\n",
       "      <td>29228951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-02-05</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>80.500000</td>\n",
       "      <td>78.800003</td>\n",
       "      <td>79.300003</td>\n",
       "      <td>77.864182</td>\n",
       "      <td>32494430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-02-06</td>\n",
       "      <td>80.599998</td>\n",
       "      <td>81.650002</td>\n",
       "      <td>79.449997</td>\n",
       "      <td>81.050003</td>\n",
       "      <td>79.582497</td>\n",
       "      <td>31218255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-02-07</td>\n",
       "      <td>80.800003</td>\n",
       "      <td>80.800003</td>\n",
       "      <td>79.449997</td>\n",
       "      <td>80.199997</td>\n",
       "      <td>78.747887</td>\n",
       "      <td>17885567</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date       Open       High        Low      Close  Adj Close    Volume\n",
       "0  2020-02-03  77.699997  79.199997  77.050003  78.500000  77.078674  35847965\n",
       "1  2020-02-04  80.550003  80.550003  78.849998  79.250000  77.815086  29228951\n",
       "2  2020-02-05  80.000000  80.500000  78.800003  79.300003  77.864182  32494430\n",
       "3  2020-02-06  80.599998  81.650002  79.449997  81.050003  79.582497  31218255\n",
       "4  2020-02-07  80.800003  80.800003  79.449997  80.199997  78.747887  17885567"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load dataset (past 1 year data)\n",
    "data3 = pd.read_csv(\"./stock_data/1299.HK.1year.csv\") \n",
    "data3.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>266.000000</td>\n",
       "      <td>266.000000</td>\n",
       "      <td>266.000000</td>\n",
       "      <td>266.000000</td>\n",
       "      <td>266.000000</td>\n",
       "      <td>2.660000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>80.240226</td>\n",
       "      <td>80.978196</td>\n",
       "      <td>78.927068</td>\n",
       "      <td>79.921241</td>\n",
       "      <td>79.434325</td>\n",
       "      <td>2.693857e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>10.934664</td>\n",
       "      <td>10.989758</td>\n",
       "      <td>10.711176</td>\n",
       "      <td>10.924873</td>\n",
       "      <td>11.272387</td>\n",
       "      <td>1.310346e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>61.099998</td>\n",
       "      <td>63.099998</td>\n",
       "      <td>60.049999</td>\n",
       "      <td>60.700001</td>\n",
       "      <td>59.600964</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>72.275000</td>\n",
       "      <td>72.612499</td>\n",
       "      <td>71.012501</td>\n",
       "      <td>71.900002</td>\n",
       "      <td>71.129394</td>\n",
       "      <td>1.823790e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>77.450001</td>\n",
       "      <td>78.250000</td>\n",
       "      <td>76.625000</td>\n",
       "      <td>77.549999</td>\n",
       "      <td>77.065685</td>\n",
       "      <td>2.375759e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>88.324998</td>\n",
       "      <td>88.900000</td>\n",
       "      <td>86.387501</td>\n",
       "      <td>87.824997</td>\n",
       "      <td>87.824997</td>\n",
       "      <td>3.198056e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>108.400002</td>\n",
       "      <td>109.300003</td>\n",
       "      <td>104.500000</td>\n",
       "      <td>108.900002</td>\n",
       "      <td>108.900002</td>\n",
       "      <td>8.448093e+07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Open        High         Low       Close   Adj Close  \\\n",
       "count  266.000000  266.000000  266.000000  266.000000  266.000000   \n",
       "mean    80.240226   80.978196   78.927068   79.921241   79.434325   \n",
       "std     10.934664   10.989758   10.711176   10.924873   11.272387   \n",
       "min     61.099998   63.099998   60.049999   60.700001   59.600964   \n",
       "25%     72.275000   72.612499   71.012501   71.900002   71.129394   \n",
       "50%     77.450001   78.250000   76.625000   77.549999   77.065685   \n",
       "75%     88.324998   88.900000   86.387501   87.824997   87.824997   \n",
       "max    108.400002  109.300003  104.500000  108.900002  108.900002   \n",
       "\n",
       "             Volume  \n",
       "count  2.660000e+02  \n",
       "mean   2.693857e+07  \n",
       "std    1.310346e+07  \n",
       "min    0.000000e+00  \n",
       "25%    1.823790e+07  \n",
       "50%    2.375759e+07  \n",
       "75%    3.198056e+07  \n",
       "max    8.448093e+07  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Describe dataset\n",
    "data3.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>ds</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-02-03</td>\n",
       "      <td>78.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-02-04</td>\n",
       "      <td>79.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-02-05</td>\n",
       "      <td>79.300003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-02-06</td>\n",
       "      <td>81.050003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-02-07</td>\n",
       "      <td>80.199997</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           ds          y\n",
       "0  2020-02-03  78.500000\n",
       "1  2020-02-04  79.250000\n",
       "2  2020-02-05  79.300003\n",
       "3  2020-02-06  81.050003\n",
       "4  2020-02-07  80.199997"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select date and price features from dataset\n",
    "data3 = data3[[\"Date\", \"Close\"]]\n",
    "# Rename the features for the model fitting\n",
    "data3 = data3.rename(columns = {\"Date\":\"ds\", \"Close\":\"y\"})\n",
    "data3.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:fbprophet:Disabling yearly seasonality. Run prophet with yearly_seasonality=True to override this.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<fbprophet.forecaster.Prophet at 0x7f85cc323070>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fit the model using all data (past 1 year data)\n",
    "m3 = Prophet(daily_seasonality = True)\n",
    "m3.fit(data3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the model with next 30 days forcast\n",
    "future = m3.make_future_dataframe(periods=30)\n",
    "prediction = m3.predict(future)\n",
    "m3.plot(prediction)\n",
    "plt.title(\"Prediction of the AIA Group Limited (1299.HK) Stock Price using the Prophet\")\n",
    "plt.xlabel(\"Date\")\n",
    "plt.ylabel(\"Close Stock Price\")\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}