From dddcba3d6a38f6890184171f7146fb6ae015b263 Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Sun, 2 Jan 2022 09:59:02 +0100 Subject: [PATCH 01/24] Making pa active + pa minor features Makes pa actice and adds country to the df. The groupby command also gets percents of holding allocation. It also fixes warnings and prepares for a later pr that I'm currently working on. --- .../portfolio_analysis/pa_controller.py | 19 +++++++++++++- .../portfolio_analysis/portfolio_model.py | 12 ++++++++- .../portfolio_analysis/portfolio_view.py | 11 +++++--- .../portfolio_analysis/yfinance_model.py | 26 +++++++++++++++++++ .../portfolio/portfolio_controller.py | 11 ++++++-- .../portfolio/portfolio_model.py | 10 +++---- .../portfolio/portfolios/market.csv | 2 +- .../portfolio/yfinance_model.py | 18 +++++++++++++ 8 files changed, 96 insertions(+), 13 deletions(-) create mode 100644 gamestonk_terminal/portfolio/portfolio_analysis/yfinance_model.py diff --git a/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py b/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py index 98b477277029..c07411123195 100644 --- a/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py +++ b/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py @@ -136,6 +136,14 @@ def call_load(self, other_args): help="Add sector to dataframe", dest="sector", ) + parser.add_argument( + "-c", + "--country", + action="store_true", + default=False, + help="Add country to dataframe", + dest="country", + ) parser.add_argument( "--no_last_price", action="store_false", @@ -168,6 +176,7 @@ def call_load(self, other_args): self.portfolio = portfolio_model.load_portfolio( full_path=os.path.join(portfolios_path, ns_parser.path), sector=ns_parser.sector, + country=ns_parser.country, last_price=ns_parser.last_price, show_nan=ns_parser.show_nan, ) @@ -194,6 +203,14 @@ def call_group(self, other_args): choices=self.portfolio.columns, help="Column to group by", ) + parser.add_argument( + "-a", + "--allocation", + action="store_true", + default=False, + help="Add allocation column in % to dataframe", + dest="allocation", + ) # The following arguments will be used in a later PR for customizable 'reports' @@ -214,7 +231,7 @@ def call_group(self, other_args): if ns_parser: if "value" in self.portfolio.columns: portfolio_view.display_group_holdings( - portfolio=self.portfolio, group_column=ns_parser.group + portfolio=self.portfolio, group_column=ns_parser.group, allocation=allocation ) else: print( diff --git a/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_model.py b/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_model.py index e7f84466904c..5ae78c95d339 100644 --- a/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_model.py +++ b/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_model.py @@ -5,6 +5,7 @@ import pandas as pd import yfinance as yf import gamestonk_terminal.feature_flags as gtff +from gamestonk_terminal.portfolio.portfolio_analysis import yfinance_model # pylint: disable=no-member,unsupported-assignment-operation,unsubscriptable-object @@ -12,6 +13,7 @@ def load_portfolio( full_path: str, sector: bool = False, + country: bool = False, last_price: bool = False, show_nan: bool = True, ) -> pd.DataFrame: @@ -22,7 +24,9 @@ def load_portfolio( full_path : str Path to portfolio file. sector : bool, optional - Boolean to indicate getting sector from yfinance , by default False + Boolean to indicate getting sector from yfinance, by default False + country : bool, optional + Boolean to indicate getting country from yfinance, by default False last_price : bool, optional Boolean to indicate getting last price from yfinance, by default False show_nan : bool, optional @@ -50,6 +54,12 @@ def load_portfolio( axis=1, ) + if country: + df["country"] = df.apply( + lambda row: yfinance_model.get_country(row.Ticker), + axis=1, + ) + if last_price: df["last_price"] = df.apply( lambda row: yf.Ticker(row.Ticker) diff --git a/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_view.py b/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_view.py index b03131ea12c2..b7421b3acdd4 100644 --- a/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_view.py +++ b/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_view.py @@ -6,7 +6,7 @@ import gamestonk_terminal.feature_flags as gtff -def display_group_holdings(portfolio: pd.DataFrame, group_column: str): +def display_group_holdings(portfolio: pd.DataFrame, group_column: str, allocation: bool): """Display portfolio holdings based on grouping Parameters @@ -16,13 +16,18 @@ def display_group_holdings(portfolio: pd.DataFrame, group_column: str): group_column : str Column to group by """ - + headers = [group_column, "value"] grouped_df = pd.DataFrame(portfolio.groupby(group_column).agg(sum)["value"]) + + if allocation: + total_value = grouped_df["value"].sum() + grouped_df["% allocation"] = grouped_df["value"] / total_value * 100 + headers.append("% allocation") if gtff.USE_TABULATE_DF: print( tabulate( grouped_df, - headers=[group_column, "value"], + headers=headers, tablefmt="fancy_grid", floatfmt=".2f", ), diff --git a/gamestonk_terminal/portfolio/portfolio_analysis/yfinance_model.py b/gamestonk_terminal/portfolio/portfolio_analysis/yfinance_model.py new file mode 100644 index 000000000000..9bd7c1a3f2b6 --- /dev/null +++ b/gamestonk_terminal/portfolio/portfolio_analysis/yfinance_model.py @@ -0,0 +1,26 @@ +"""Yfinance model""" +__docformat__ = "numpy" + +from typing import List +from datetime import datetime, timedelta + +import yfinance as yf +import pandas as pd + + +def get_country(ticker): + country = "NA" + data = yf.utils.get_json(f"https://finance.yahoo.com/quote/{ticker}") + + if "summaryProfile" in data: + country = data["summaryProfile"]["country"] + if self.country not in financedatabase_model.get_countries(): + similar_cmd = difflib.get_close_matches( + country, + financedatabase_model.get_countries(), + n=1, + cutoff=0.7, + ) + if similar_cmd: + country = similar_cmd[0] + return country diff --git a/gamestonk_terminal/portfolio/portfolio_controller.py b/gamestonk_terminal/portfolio/portfolio_controller.py index 211ab1c79e68..ddaf4f9d01ff 100644 --- a/gamestonk_terminal/portfolio/portfolio_controller.py +++ b/gamestonk_terminal/portfolio/portfolio_controller.py @@ -54,6 +54,7 @@ class PortfolioController: CHOICES_MENUS = [ "bro", "po", + "pa", ] CHOICES_COMMANDS = [ "load", @@ -219,6 +220,12 @@ def call_po(self, _): """Process po command""" return po_controller.menu([], self.queue) + def call_pa(self, _): + """Process pa command""" + from gamestonk_terminal.portfolio.portfolio_analysis import pa_controller + + return pa_controller.menu() + @try_except def call_load(self, other_args: List[str]): """Process load command""" @@ -310,7 +317,7 @@ def call_add(self, other_args: List[str]): "--type", dest="type", type=lambda s: s.lower(), - choices=["stock", "cash"], # "bond", "option", "crypto", + choices=["stock", "cash", "etf"], # "bond", "option", "crypto", default="stock", help="Type of asset to add", ) @@ -455,7 +462,7 @@ def call_rmr(self, other_args: List[str]): ) ns_parser = parse_known_args_and_warn(parser, other_args) if ns_parser: - if self.portfolio.empty: + if not self.portfolio.empty: val, _ = portfolio_model.convert_df(self.portfolio) if not val.empty: df_m = yfinance_model.get_market(val.index[0], ns_parser.market) diff --git a/gamestonk_terminal/portfolio/portfolio_model.py b/gamestonk_terminal/portfolio/portfolio_model.py index cbe6096458a2..0a2fe13304e9 100644 --- a/gamestonk_terminal/portfolio/portfolio_model.py +++ b/gamestonk_terminal/portfolio/portfolio_model.py @@ -246,10 +246,10 @@ def merge_dataframes( comb[("Profit", uni)] = comb[("Profit", uni)].cumsum() comb[("Cash", "Cash")] = comb[("Cash", "Cash")].cumsum() if len(changes["Date"]) > 0: - comb["holdings"] = comb.sum(level=0, axis=1)["Holding"] - comb["profits"] = comb.sum(level=0, axis=1)["Profit"] + comb["holdings"] = comb.groupby(level=0, axis=1).sum()["Holding"] + comb["profits"] = comb.groupby(level=0, axis=1).sum()["Profit"] comb["total_prof"] = comb["holdings"] + comb["profits"] - comb["total_cost"] = comb.sum(level=0, axis=1)["Cost Basis"] + comb["total_cost"] = comb.groupby(level=0, axis=1).sum()["Cost Basis"] return comb @@ -269,11 +269,11 @@ def convert_df(portfolio: pd.DataFrame) -> pd.DataFrame: The historical performance of tickers in portfolio """ changes = portfolio.copy() - # Transactions sorted for only stocks + # Transactions sorted for only stocks and etfs cashes = changes[changes["Type"] == "cash"] if cashes.empty: raise ValueError("Brokers require cash, input cash deposits") - changes = changes[changes["Type"] == "stock"] + changes = changes[changes["Type"] == ("stock" or "etf")] uniques = list(set(changes["Name"].tolist())) if uniques: hist = yfinance_model.get_stocks(uniques, min(changes["Date"])) diff --git a/gamestonk_terminal/portfolio/portfolios/market.csv b/gamestonk_terminal/portfolio/portfolios/market.csv index a3ea9b70e640..33d4f5d78eef 100644 --- a/gamestonk_terminal/portfolio/portfolios/market.csv +++ b/gamestonk_terminal/portfolio/portfolios/market.csv @@ -1,4 +1,4 @@ Name,Type,Quantity,Date,Price,Fees,Premium,Side -spy,stock,1.0,2019/10/21,200.0,,,Buy +spy,etf,1.0,2019/10/21,200.0,,,Buy cash,cash,1.0,2019/10/21,200.0,,,deposit cash,cash,1.0,2021/6/21,200.0,,,withdrawal diff --git a/gamestonk_terminal/portfolio/yfinance_model.py b/gamestonk_terminal/portfolio/yfinance_model.py index 373a6546d51d..30967ad42814 100644 --- a/gamestonk_terminal/portfolio/yfinance_model.py +++ b/gamestonk_terminal/portfolio/yfinance_model.py @@ -83,3 +83,21 @@ def get_market(start: datetime, ticker: str = "SPY") -> pd.DataFrame: interval="1d", )["Close"] return df.to_frame(name=("Market", "Close")) + + +def get_country(ticker): + country = "NA" + data = yf.utils.get_json(f"https://finance.yahoo.com/quote/{ticker}") + + if "summaryProfile" in data: + country = data["summaryProfile"]["country"] + if self.country not in financedatabase_model.get_countries(): + similar_cmd = difflib.get_close_matches( + country, + financedatabase_model.get_countries(), + n=1, + cutoff=0.7, + ) + if similar_cmd: + country = similar_cmd[0] + return country From 818c9318874756d6be12ad409cbf4a2f4a0f5ea7 Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Sun, 2 Jan 2022 10:06:50 +0100 Subject: [PATCH 02/24] Fix linting --- .../portfolio/portfolio_analysis/pa_controller.py | 6 ++++-- .../portfolio/portfolio_analysis/portfolio_view.py | 4 +++- 2 files changed, 7 insertions(+), 3 deletions(-) diff --git a/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py b/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py index c07411123195..239ef90c66df 100644 --- a/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py +++ b/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py @@ -125,7 +125,8 @@ def call_load(self, other_args): prog="load", add_help=False, formatter_class=argparse.ArgumentDefaultsHelpFormatter, - description="Function to get portfolio from predefined csv/json/xlsx file inside portfolios folder", + description="Function to get portfolio from predefined " + "csv/json/xlsx file inside portfolios folder", epilog="usage: load file_name", ) parser.add_argument( @@ -235,7 +236,8 @@ def call_group(self, other_args): ) else: print( - "'value' column not in portfolio. Either add manually or load without --no_last_price flag\n" + "'value' column not in portfolio. " + "Either add manually or load without --no_last_price flag\n" ) @try_except diff --git a/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_view.py b/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_view.py index b7421b3acdd4..65bf8a9e3997 100644 --- a/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_view.py +++ b/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_view.py @@ -6,7 +6,9 @@ import gamestonk_terminal.feature_flags as gtff -def display_group_holdings(portfolio: pd.DataFrame, group_column: str, allocation: bool): +def display_group_holdings(portfolio: pd.DataFrame, + group_column: str, + allocation: bool,): """Display portfolio holdings based on grouping Parameters From ed957efba0aa0bac2247d4463c02c70a6a046178 Mon Sep 17 00:00:00 2001 From: DidierRLopes Date: Tue, 4 Jan 2022 23:29:10 +0000 Subject: [PATCH 03/24] black linter --- .../portfolio/portfolio_analysis/pa_controller.py | 6 ++++-- .../portfolio/portfolio_analysis/portfolio_view.py | 8 +++++--- .../portfolio/portfolio_analysis/yfinance_model.py | 8 +++----- gamestonk_terminal/portfolio/yfinance_model.py | 4 +++- 4 files changed, 15 insertions(+), 11 deletions(-) diff --git a/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py b/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py index 316530fdab5a..a8cd6491521a 100644 --- a/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py +++ b/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py @@ -126,7 +126,7 @@ def call_load(self, other_args): add_help=False, formatter_class=argparse.ArgumentDefaultsHelpFormatter, description="Function to get portfolio from predefined " - "csv/json/xlsx file inside portfolios folder", + "csv/json/xlsx file inside portfolios folder", epilog="usage: load file_name", ) parser.add_argument( @@ -232,7 +232,9 @@ def call_group(self, other_args): if ns_parser: if "value" in self.portfolio.columns: portfolio_view.display_group_holdings( - portfolio=self.portfolio, group_column=ns_parser.group, allocation=allocation + portfolio=self.portfolio, + group_column=ns_parser.group, + allocation=ns_parser.allocation, ) else: print( diff --git a/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_view.py b/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_view.py index 65bf8a9e3997..d097d482b6aa 100644 --- a/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_view.py +++ b/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_view.py @@ -6,9 +6,11 @@ import gamestonk_terminal.feature_flags as gtff -def display_group_holdings(portfolio: pd.DataFrame, - group_column: str, - allocation: bool,): +def display_group_holdings( + portfolio: pd.DataFrame, + group_column: str, + allocation: bool, +): """Display portfolio holdings based on grouping Parameters diff --git a/gamestonk_terminal/portfolio/portfolio_analysis/yfinance_model.py b/gamestonk_terminal/portfolio/portfolio_analysis/yfinance_model.py index 9bd7c1a3f2b6..06692d71b86d 100644 --- a/gamestonk_terminal/portfolio/portfolio_analysis/yfinance_model.py +++ b/gamestonk_terminal/portfolio/portfolio_analysis/yfinance_model.py @@ -1,11 +1,9 @@ """Yfinance model""" __docformat__ = "numpy" -from typing import List -from datetime import datetime, timedelta - +import difflib import yfinance as yf -import pandas as pd +from gamestonk_terminal.stocks.sector_industry_analysis import financedatabase_model def get_country(ticker): @@ -14,7 +12,7 @@ def get_country(ticker): if "summaryProfile" in data: country = data["summaryProfile"]["country"] - if self.country not in financedatabase_model.get_countries(): + if country not in financedatabase_model.get_countries(): similar_cmd = difflib.get_close_matches( country, financedatabase_model.get_countries(), diff --git a/gamestonk_terminal/portfolio/yfinance_model.py b/gamestonk_terminal/portfolio/yfinance_model.py index 30967ad42814..a998c0380d00 100644 --- a/gamestonk_terminal/portfolio/yfinance_model.py +++ b/gamestonk_terminal/portfolio/yfinance_model.py @@ -1,11 +1,13 @@ """Yfinance model""" __docformat__ = "numpy" +import difflib from typing import List from datetime import datetime, timedelta import yfinance as yf import pandas as pd +from gamestonk_terminal.stocks.sector_industry_analysis import financedatabase_model def get_stocks(tickers: List[str], start: datetime) -> pd.DataFrame: @@ -91,7 +93,7 @@ def get_country(ticker): if "summaryProfile" in data: country = data["summaryProfile"]["country"] - if self.country not in financedatabase_model.get_countries(): + if country not in financedatabase_model.get_countries(): similar_cmd = difflib.get_close_matches( country, financedatabase_model.get_countries(), From d7060a1ab373304b49644b45399586fb79b3e791 Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Sat, 8 Jan 2022 14:12:15 +0100 Subject: [PATCH 04/24] Fixes Should fix everything --- .../portfolio/portfolio_analysis/portfolio_model.py | 6 ++---- .../portfolio/portfolio_analysis/portfolio_view.py | 4 ++-- gamestonk_terminal/portfolio/portfolio_controller.py | 1 + 3 files changed, 5 insertions(+), 6 deletions(-) diff --git a/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_model.py b/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_model.py index 5ae78c95d339..ff99188ad0fa 100644 --- a/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_model.py +++ b/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_model.py @@ -55,10 +55,8 @@ def load_portfolio( ) if country: - df["country"] = df.apply( - lambda row: yfinance_model.get_country(row.Ticker), - axis=1, - ) + country_dict = {tick: yfinance_model.get_country(tick) for tick in df.Ticker.unique()} + df["Country"] = df["Ticker"].map(country_dict) if last_price: df["last_price"] = df.apply( diff --git a/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_view.py b/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_view.py index d097d482b6aa..d3340bc0f68c 100644 --- a/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_view.py +++ b/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_view.py @@ -25,8 +25,8 @@ def display_group_holdings( if allocation: total_value = grouped_df["value"].sum() - grouped_df["% allocation"] = grouped_df["value"] / total_value * 100 - headers.append("% allocation") + grouped_df["pct_allocation"] = grouped_df["value"] / total_value * 100 + headers.append("pct_allocation") if gtff.USE_TABULATE_DF: print( tabulate( diff --git a/gamestonk_terminal/portfolio/portfolio_controller.py b/gamestonk_terminal/portfolio/portfolio_controller.py index 7bbbd9c62508..613829795455 100644 --- a/gamestonk_terminal/portfolio/portfolio_controller.py +++ b/gamestonk_terminal/portfolio/portfolio_controller.py @@ -106,6 +106,7 @@ def print_help(self): > bro brokers holdings, \t\t supports: robinhood, ally, degiro, coinbase > po portfolio optimization, \t optimal portfolio weights from pyportfolioopt +> pa portfolio analysis, \t\t analyse portfolios Portfolio: load load data into the portfolio From 31bc1b6e506dcb7a240bce6216e4f5125a2c18b1 Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Sat, 8 Jan 2022 19:49:21 +0100 Subject: [PATCH 05/24] Linting --- .../portfolio/portfolio_analysis/portfolio_model.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_model.py b/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_model.py index ff99188ad0fa..bd234045c30b 100644 --- a/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_model.py +++ b/gamestonk_terminal/portfolio/portfolio_analysis/portfolio_model.py @@ -55,7 +55,9 @@ def load_portfolio( ) if country: - country_dict = {tick: yfinance_model.get_country(tick) for tick in df.Ticker.unique()} + country_dict = { + tick: yfinance_model.get_country(tick) for tick in df.Ticker.unique() + } df["Country"] = df["Ticker"].map(country_dict) if last_price: From 43ae0cbbc7fafe3f8b6feb127bd9c76fe73fbefa Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Sun, 9 Jan 2022 12:19:18 +0100 Subject: [PATCH 06/24] Making pa controller to base class standard --- .../portfolio_analysis/pa_controller.py | 112 +++--------------- 1 file changed, 19 insertions(+), 93 deletions(-) diff --git a/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py b/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py index a8cd6491521a..cdfff3d30e29 100644 --- a/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py +++ b/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py @@ -3,16 +3,18 @@ import argparse import os +from os import listdir +from os.path import isfile, join +from typing import List +from datetime import datetime -import pandas as pd from prompt_toolkit.completion import NestedCompleter - +import pandas as pd +from gamestonk_terminal.parent_classes import BaseController from gamestonk_terminal import feature_flags as gtff from gamestonk_terminal.helper_funcs import ( - get_flair, - parse_known_args_and_warn, - try_except, - system_clear, + valid_date, + check_positive_float, ) from gamestonk_terminal.menu import session from gamestonk_terminal.portfolio.portfolio_analysis import ( @@ -20,6 +22,9 @@ portfolio_view, ) +from gamestonk_terminal.helper_funcs import parse_known_args_and_warn + + portfolios_path = os.path.join(os.path.abspath(os.path.dirname(__file__)), "portfolios") possible_paths = [ port @@ -28,30 +33,26 @@ ] -class PortfolioController: +class PortfolioController(BaseController): """Portfolio Controller""" - CHOICES = [ - "cls", - "?", - "help", - "q", - "quit", - ] CHOICES_COMMANDS = [ "view", "load", "group", ] - CHOICES += CHOICES_COMMANDS + def __init__(self, queue: List[str] = None): + + super().__init__("/portfolio/", queue) - def __init__(self): - self.pa_parser = argparse.ArgumentParser(add_help=False, prog="pa") - self.pa_parser.add_argument("cmd", choices=self.CHOICES) self.portfolio_name = "" self.portfolio = pd.DataFrame() + if session and gtff.USE_PROMPT_TOOLKIT: + choices: dict = {c: {} for c in self.controller_choices} + self.completer = NestedCompleter.from_nested_dict(choices) + def print_help(self): """Print help""" help_string = f""" @@ -72,53 +73,6 @@ def print_help(self): """ print(help_string) - def switch(self, an_input: str): - """Process and dispatch input - - Returns - ------- - True, False or None - False - quit the menu - True - quit the program - None - continue in the menu - """ - - # Empty command - if not an_input: - print("") - return - - (known_args, other_args) = self.pa_parser.parse_known_args(an_input.split()) - - # Help menu again - if known_args.cmd == "?": - self.print_help() - return - - # Clear screen - if known_args.cmd == "cls": - system_clear() - return - - getattr( - self, - "call_" + known_args.cmd, - lambda _: "Command not recognized!", - )(other_args) - - return - - def call_help(self, _): - """Process Help command""" - self.print_help() - - def call_q(self, _): - """Process Q command - quit the menu""" - - def call_quit(self, _): - """Process Quit command - quit the program""" - - @try_except def call_load(self, other_args): """Process load command""" parser = argparse.ArgumentParser( @@ -184,7 +138,6 @@ def call_load(self, other_args): if not self.portfolio.empty: print(f"Successfully loaded: {self.portfolio_name}\n") - @try_except def call_group(self, other_args): """Process group command""" parser = argparse.ArgumentParser( @@ -242,7 +195,6 @@ def call_group(self, other_args): "Either add manually or load without --no_last_price flag\n" ) - @try_except def call_view(self, other_args): parser = argparse.ArgumentParser( prog="view", @@ -273,29 +225,3 @@ def call_view(self, other_args): for port in available_ports: print(port) print("") - - -def menu(): - """Portfolio Analysis Menu""" - pa_controller = PortfolioController() - pa_controller.print_help() - - while True: - # Get input command from user - if session and gtff.USE_PROMPT_TOOLKIT: - completer = NestedCompleter.from_nested_dict( - {c: None for c in pa_controller.CHOICES} - ) - an_input = session.prompt( - f"{get_flair()} (portfolio)>(pa)> ", - completer=completer, - ) - else: - an_input = input(f"{get_flair()} (portfolio)>(pa)> ") - - try: - pa_controller.switch(an_input) - - except SystemExit: - print("The command selected doesn't exist\n") - continue From dedb0805ac1f853c2c61cc680b29bbb29d48f84d Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Sun, 9 Jan 2022 20:07:13 +0100 Subject: [PATCH 07/24] Fix linting --- .../portfolio/portfolio_analysis/pa_controller.py | 9 +-------- gamestonk_terminal/portfolio/portfolio_controller.py | 3 ++- 2 files changed, 3 insertions(+), 9 deletions(-) diff --git a/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py b/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py index aa4604ea75cd..f3e3df646d2c 100644 --- a/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py +++ b/gamestonk_terminal/portfolio/portfolio_analysis/pa_controller.py @@ -4,23 +4,16 @@ from typing import List import argparse import os -from os import listdir -from os.path import isfile, join -from typing import List -from datetime import datetime from prompt_toolkit.completion import NestedCompleter import pandas as pd from gamestonk_terminal.parent_classes import BaseController from gamestonk_terminal import feature_flags as gtff -from gamestonk_terminal.helper_funcs import ( - valid_date, - check_positive_float, -) from gamestonk_terminal.portfolio.portfolio_analysis import ( portfolio_model, portfolio_view, ) +from gamestonk_terminal.menu import session from gamestonk_terminal.helper_funcs import parse_known_args_and_warn diff --git a/gamestonk_terminal/portfolio/portfolio_controller.py b/gamestonk_terminal/portfolio/portfolio_controller.py index f3c3995d7713..6654d209666d 100644 --- a/gamestonk_terminal/portfolio/portfolio_controller.py +++ b/gamestonk_terminal/portfolio/portfolio_controller.py @@ -45,6 +45,7 @@ class PortfolioController(BaseController): CHOICES_MENUS = [ "bro", "po", + "pa", ] def __init__(self, queue: List[str] = None): @@ -108,7 +109,7 @@ def call_pa(self, _): """Process pa command""" from gamestonk_terminal.portfolio.portfolio_analysis import pa_controller - self.queue = pa_controller.PortfolioAnalysis([], self.queue).menu() + self.queue = pa_controller.PortfolioAnalysis(self.queue).menu() def call_load(self, other_args: List[str]): """Process load command""" From 41ee276bf61f99134ed6512163cdddb350eb7c70 Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Thu, 30 Jun 2022 09:19:58 +0200 Subject: [PATCH 08/24] first metrics --- openbb_terminal/portfolio/portfolio_helper.py | 4 +- openbb_terminal/portfolio/portfolio_model.py | 321 +++++++++++++++--- 2 files changed, 285 insertions(+), 40 deletions(-) diff --git a/openbb_terminal/portfolio/portfolio_helper.py b/openbb_terminal/portfolio/portfolio_helper.py index 32773f726c59..8f349fe03209 100644 --- a/openbb_terminal/portfolio/portfolio_helper.py +++ b/openbb_terminal/portfolio/portfolio_helper.py @@ -194,7 +194,7 @@ def filter_df_by_period(df: pd.DataFrame, period: str = "all") -> pd.DataFrame: Returns ---------- - str + pd.DataFrame A cleaned value """ if period == "mtd": @@ -284,7 +284,7 @@ def get_maximum_drawdown(return_series: pd.Series) -> float: Returns ------- float - maximum drawdown + Maximum drawdown """ comp_ret = (return_series + 1).cumprod() peak = comp_ret.expanding(min_periods=1).max() diff --git a/openbb_terminal/portfolio/portfolio_model.py b/openbb_terminal/portfolio/portfolio_model.py index 22899dde64e3..bfbf9bc407e2 100644 --- a/openbb_terminal/portfolio/portfolio_model.py +++ b/openbb_terminal/portfolio/portfolio_model.py @@ -27,7 +27,7 @@ @log_start_end(log=logger) def get_rolling_beta( - df: pd.DataFrame, hist: pd.DataFrame, mark: pd.DataFrame, n: pd.DataFrame + df: pd.DataFrame, hist: pd.DataFrame, mark: pd.DataFrame, n: pd.DataFrame ) -> pd.DataFrame: """Turns the holdings of a portfolio into a rolling beta dataframe @@ -182,6 +182,24 @@ def calculate_drawdown(input_series: pd.Series, is_returns: bool = False) -> pd. return drawdown +def get_gaintopain_ratio(desired_return: float, tolerable_maximum_draw_down: float): + """Gets Pain-to-Gain ratio + + Parameters + ---------- + desired_return: float + Desired return + tolerable_maximum_draw_down: float + Maximum tolerable draw down + + Returns + ------- + float + Pain-to-Gain ratio + """ + return desired_return / tolerable_maximum_draw_down + + class Portfolio: """ Class for portfolio analysis in OpenBB @@ -348,8 +366,8 @@ def generate_holdings_from_trades(self, yfinance_use_close: bool = False): portfolio[ pd.MultiIndex.from_product([["StockHoldings"], self._stock_tickers]) ] = ( - portfolio["Quantity"][self._stock_tickers] - * portfolio["Close"][self._stock_tickers] + portfolio["Quantity"][self._stock_tickers] + * portfolio["Close"][self._stock_tickers] ) else: portfolio[pd.MultiIndex.from_product([["StockHoldings"], ["temp"]])] = 0 @@ -359,8 +377,8 @@ def generate_holdings_from_trades(self, yfinance_use_close: bool = False): portfolio[ pd.MultiIndex.from_product([["ETFHoldings"], self._etf_tickers]) ] = ( - portfolio["Quantity"][self._etf_tickers] - * portfolio["Close"][self._etf_tickers] + portfolio["Quantity"][self._etf_tickers] + * portfolio["Close"][self._etf_tickers] ) else: portfolio[pd.MultiIndex.from_product([["ETFHoldings"], ["temp"]])] = 0 @@ -369,8 +387,8 @@ def generate_holdings_from_trades(self, yfinance_use_close: bool = False): portfolio[ pd.MultiIndex.from_product([["CryptoHoldings"], self._crypto_tickers]) ] = ( - portfolio["Quantity"][self._crypto_tickers] - * portfolio["Close"][self._crypto_tickers] + portfolio["Quantity"][self._crypto_tickers] + * portfolio["Close"][self._crypto_tickers] ) else: portfolio[pd.MultiIndex.from_product([["CryptoHoldings"], ["temp"]])] = 0 @@ -380,11 +398,11 @@ def generate_holdings_from_trades(self, yfinance_use_close: bool = False): # stocks bought + stocks sold if "CASH" not in portfolio["Investment"]: portfolio["CashHold"] = ( - portfolio["Investment"][ - self._stock_tickers + self._etf_tickers + self._crypto_tickers - ].sum(axis=1) - + portfolio["Fees"].sum(axis=1) - + portfolio["Premium"].sum(axis=1) + portfolio["Investment"][ + self._stock_tickers + self._etf_tickers + self._crypto_tickers + ].sum(axis=1) + + portfolio["Fees"].sum(axis=1) + + portfolio["Premium"].sum(axis=1) ) else: portfolio["CashHold"] = portfolio["Investment"]["CASH"] - portfolio[ @@ -395,17 +413,17 @@ def generate_holdings_from_trades(self, yfinance_use_close: bool = False): # Subtract Fees or Premiums from cash holdings portfolio["CashHold"] = ( - portfolio["CashHold"] - - portfolio["Fees"].sum(axis=1) - - portfolio["Premium"].sum(axis=1) + portfolio["CashHold"] + - portfolio["Fees"].sum(axis=1) + - portfolio["Premium"].sum(axis=1) ) portfolio["CashHold"] = portfolio["CashHold"].cumsum() portfolio["TotalHoldings"] = ( - portfolio["CashHold"] - + portfolio["StockHoldings"].sum(axis=1) - + portfolio["ETFHoldings"].sum(axis=1) - + portfolio["CryptoHoldings"].sum(axis=1) + portfolio["CashHold"] + + portfolio["StockHoldings"].sum(axis=1) + + portfolio["ETFHoldings"].sum(axis=1) + + portfolio["CryptoHoldings"].sum(axis=1) ) self.portfolio_value = portfolio["TotalHoldings"] @@ -444,15 +462,17 @@ def generate_holdings_from_trades(self, yfinance_use_close: bool = False): "Investment" ] self.portfolio_trades["Portfolio Value"][index] = ( - self.portfolio_trades["Close"][index] * trade["Quantity"] + self.portfolio_trades["Close"][index] * trade["Quantity"] ) self.portfolio_trades["% Portfolio Return"][index] = ( - self.portfolio_trades["Portfolio Value"][index] - / self.portfolio_trades["Portfolio Investment"][index] - ) - 1 + self.portfolio_trades["Portfolio Value"][ + index] + / self.portfolio_trades[ + "Portfolio Investment"][index] + ) - 1 self.portfolio_trades["Abs Portfolio Return"].loc[index] = ( - self.portfolio_trades["Portfolio Value"][index] - - self.portfolio_trades["Portfolio Investment"][index] + self.portfolio_trades["Portfolio Value"][index] + - self.portfolio_trades["Portfolio Investment"][index] ) self.portfolio = portfolio.copy() @@ -562,7 +582,7 @@ def mimic_portfolio_trades_for_benchmark(self, full_shares: bool = False): if not full_shares: self.benchmark_trades["Benchmark Quantity"][index] = ( - trade["Investment"] / self.benchmark_trades["Price"][index] + trade["Investment"] / self.benchmark_trades["Price"][index] ) else: self.benchmark_trades["Benchmark Quantity"][index] = np.floor( @@ -570,20 +590,22 @@ def mimic_portfolio_trades_for_benchmark(self, full_shares: bool = False): ) self.benchmark_trades["Benchmark Investment"][index] = ( - self.benchmark_trades["Price"][index] - * self.benchmark_trades["Benchmark Quantity"][index] + self.benchmark_trades["Price"][index] + * self.benchmark_trades["Benchmark Quantity"][index] ) self.benchmark_trades["Benchmark Value"][index] = ( - self.benchmark_trades["Close"][index] - * self.benchmark_trades["Benchmark Quantity"][index] + self.benchmark_trades["Close"][index] + * self.benchmark_trades["Benchmark Quantity"][index] ) self.benchmark_trades["% Benchmark Return"][index] = ( - self.benchmark_trades["Benchmark Value"][index] - / self.benchmark_trades["Benchmark Investment"][index] - ) - 1 + self.benchmark_trades["Benchmark Value"][ + index] + / self.benchmark_trades[ + "Benchmark Investment"][index] + ) - 1 self.benchmark_trades["Abs Benchmark Return"][index] = ( - self.benchmark_trades["Benchmark Value"][index] - - self.benchmark_trades["Benchmark Investment"][index] + self.benchmark_trades["Benchmark Value"][index] + - self.benchmark_trades["Benchmark Investment"][index] ) # pylint:disable=no-member @@ -780,9 +802,9 @@ def get_stats(self, period: str = "all") -> pd.DataFrame: """ df = ( portfolio_helper.filter_df_by_period(self.returns, period) - .describe() - .to_frame() - .join( + .describe() + .to_frame() + .join( portfolio_helper.filter_df_by_period( self.benchmark_returns, period ).describe() @@ -936,3 +958,226 @@ def get_maximum_drawdown_ratio(self) -> pd.DataFrame: return pd.DataFrame( vals, index=portfolio_helper.PERIODS, columns=["Portfolio", "Benchmark"] ) + + @log_start_end(log=logger) + def get_rolling_beta(self, period: float = 252): + """Get rolling beta + + Parameters + ---------- + period: float + Interval used for rolling values + + Returns + ------- + pd.DataFrame + DataFrame of the portfolio's rolling beta + """ + + # Rolling beta is defined as Cov(Port,Bench)/var(Bench) + covs = ( + pd.DataFrame({"Portfolio": self.returns, "Benchmark": self.benchmark_returns}) + .dropna(axis=0) + .rolling(period) + .cov() + .unstack() + .dropna() + ) + rolling_beta = covs["Portfolio"]["Benchmark"] / covs["Benchmark"]["Benchmark"] + + return rolling_beta + + @log_start_end(log=logger) + def get_tracking_error(self, period: float = 252): + """Get tracking error + + Parameters + ---------- + period: float + Interval used for rolling values + + Returns + ------- + pd.DataFrame + DataFrame of tracking errors during different time periods + pd.Series + Series of rolling tracking error + """ + diff_returns = self.returns - self.benchmark_returns + + vals = list() + for period in portfolio_helper.PERIODS: + vals.append( + [ + round( + portfolio_helper.filter_df_by_period(self.returns, period).std(), + 3, + ) + ] + ) + trackr_period_df = pd.DataFrame(vals, index=portfolio_helper.PERIODS, columns=["Tracking Error"]) + + return trackr_period_df, diff_returns.rolling(period, min_periods=period).std() + + @log_start_end(log=logger) + def get_information_ratio(self, period: float = 252): + """ + + Parameters + ---------- + period: float + Interval used for rolling values + + Returns + ------- + pd.DataFrame + DataFrame of the information ratio during different time periods + pd.Series + Series of rolling information ratio + """ + diff_returns = self.returns - self.benchmark_returns + + _, tracking_err = self.get_tracking_error(period=period) + + vals = list() + for period in portfolio_helper.PERIODS: + vals.append( + [ + round( + portfolio_helper.filter_df_by_period(diff_returns, period) / + portfolio_helper.filter_df_by_period(tracking_err, period), + 3, + ) + ] + ) + + ir_period_df = pd.DataFrame(vals, index=portfolio_helper.PERIODS, columns=["Information Ratio"]) + ir_rolling = ((1 + diff_returns.rolling(period, min_periods=period).shift(periods=1, fill_value=0)).cumprod() - 1) / tracking_err + + return ir_period_df, ir_rolling + + @log_start_end(log=logger) + def get_tail_ratio(self, period: float = 252): + """ + + Parameters + ---------- + period: float + Interval used for rolling values + + Returns + ------- + pd.DataFrame + DataFrame of the portfolios and the benchmarks tail ratio during different time periods + pd.Series + Series of the portfolios rolling tail ratio + pd.Series + Series of the benchmarks rolling tail ratio + """ + returns = self.returns.rolling(period, min_periods=period) + benchmark_returns = self.benchmark_returns.rolling(period, min_periods=period) + + portfolio_tr = returns.quantile(0.95) / returns.quantile(0.05) + benchmark_tr = benchmark_returns.quantile(0.95) / benchmark_returns.quantile(0.05) + + vals = list() + for period in portfolio_helper.PERIODS: + vals.append( + [ + round( + portfolio_helper.filter_df_by_period(self.returns, period).quantile(0.95) / + portfolio_helper.filter_df_by_period(self.returns, period).quantile(0.05), + 3, + ), + round( + portfolio_helper.filter_df_by_period(self.benchmark_returns, period).quantile(0.95) / + portfolio_helper.filter_df_by_period(self.benchmark_returns, period).quantile(0.05), + 3, + ), + ] + ) + + tailr_period_df = pd.DataFrame(vals, index=portfolio_helper.PERIODS, columns=["Portfolio", "Benchmark"]) + + return tailr_period_df, portfolio_tr, benchmark_tr + + @log_start_end(log=logger) + def get_common_sense_ratio(self, period: float = 252): + tail_ratio_df, portfolio_tr, benchmark_tr = self.get_tail_ratio(period) + + vals = list() + for period in portfolio_helper.PERIODS: + period_return = portfolio_helper.filter_df_by_period(self.returns, period) + period_bench_return = portfolio_helper.filter_df_by_period(self.benchmark_returns, period) + vals.append( + [ + round( + tail_ratio_df.loc[period, "Portfolio"] * + get_gaintopain_ratio( + ((1 + period_return.shift(periods=1, fill_value=0)).cumprod() - 1).iloc[-1], + portfolio_helper.get_maximum_drawdown(period_return)), + 3, + ), + round( + tail_ratio_df.loc[period, "Benchmark"] * + get_gaintopain_ratio( + ((1 + period_bench_return.shift(periods=1, fill_value=0)).cumprod() - 1).iloc[-1], + portfolio_helper.get_maximum_drawdown(period_bench_return)), + 3, + ), + ] + ) + + csr_period_df = pd.DataFrame(vals, index=portfolio_helper.PERIODS, columns=["Portfolio", "Benchmark"]) + + return csr_period_df + + @log_start_end(log=logger) + def get_jensens_alpha(self, period: float = 252): + """Get jensen's alpha + + Parameters + ---------- + period: float + Interval used for rolling values + + Returns + ------- + pd.DataFrame + DataFrame of jensens's alpha during different time periods + pd.Series + Series of jensens's alpha data + """ + period_cum_returns = ((1 + self.returns.rolling(period, min_periods=period) + .shift(periods=1, fill_value=0)).cumprod() - 1) + period_cum_bench_returns = ((1 + self.benchmark_returns.rolling(period, min_periods=period) + .shift(periods=1, fill_value=0)).cumprod() - 1) + rfr_cum_returns = self.rf * period / 252 + beta = self.get_rolling_beta(period) + + ja_rolling = period_cum_returns - (rfr_cum_returns + beta * (period_cum_bench_returns - rfr_cum_returns)) + + vals = list() + for period in portfolio_helper.PERIODS: + period_return = portfolio_helper.filter_df_by_period(self.returns, period) + period_bench_return = portfolio_helper.filter_df_by_period(self.benchmark_returns, period) + period_cum_returns = ((1 + period_return.shift(periods=1, fill_value=0)).cumprod() - 1) + period_cum_bench_returns = ((1 + period_bench_return.shift(periods=1, fill_value=0)).cumprod() - 1) + rfr_cum_returns = self.rf * portfolio_helper.PERIODS_DAYS[period] / 252 + beta = self.get_rolling_beta(portfolio_helper.PERIODS_DAYS[period]).iloc[-1, 0] + vals.append( + [ + round( + period_cum_returns - (rfr_cum_returns + beta * (period_cum_bench_returns - rfr_cum_returns)), + 3, + ) + ] + ) + + ja_period_df = pd.DataFrame(vals, index=portfolio_helper.PERIODS, columns=["Portfolio"]) + + return ja_period_df, ja_rolling + + @log_start_end(log=logger) + def get_calmar_ratio(self, period: float = 756): + From 29652af49c77cb48cf47c637452bc2e4d260c041 Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Thu, 30 Jun 2022 11:38:41 +0200 Subject: [PATCH 09/24] Adding calmar ratio --- openbb_terminal/portfolio/portfolio_model.py | 33 ++++++++++++++++++++ 1 file changed, 33 insertions(+) diff --git a/openbb_terminal/portfolio/portfolio_model.py b/openbb_terminal/portfolio/portfolio_model.py index bfbf9bc407e2..db40fca0cf35 100644 --- a/openbb_terminal/portfolio/portfolio_model.py +++ b/openbb_terminal/portfolio/portfolio_model.py @@ -1180,4 +1180,37 @@ def get_jensens_alpha(self, period: float = 252): @log_start_end(log=logger) def get_calmar_ratio(self, period: float = 756): + period_return = self.returns.rolling(period, min_periods=period) + period_cum_returns = ((1 + period_return.shift(periods=1, fill_value=0)).cumprod() - 1) + + # Calculate annual return + annual_return = (period_cum_returns + 1) ** (1 / (period / 252)) - 1 + + cr_rolling = annual_return / portfolio_helper.get_maximum_drawdown(period_return) + + vals = list() + for period in portfolio_helper.PERIODS: + period_return = portfolio_helper.filter_df_by_period(self.returns, period) + period_bench_return = portfolio_helper.filter_df_by_period(self.benchmark_returns, period) + annual_return = (period_cum_returns + 1) ** (1 / (period / 252)) - 1 + annual_bench_return = (period_cum_returns + 1) ** (1 / (period / 252)) - 1 + vals.append( + [ + round( + annual_return / portfolio_helper.get_maximum_drawdown(period_return), + 3, + ), + round( + annual_bench_return / portfolio_helper.get_maximum_drawdown(period_bench_return), + 3, + ), + ] + ) + + cr_period_df = pd.DataFrame(vals, index=portfolio_helper.PERIODS, columns=["Portfolio", "Benchmark"]) + + return cr_period_df, cr_rolling + + + From e9d7e4940a8cc514d27cf797b0e471df6d14d7ab Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Sat, 2 Jul 2022 09:56:21 +0200 Subject: [PATCH 10/24] Adding metrics to controller --- .../portfolio/portfolio_controller.py | 58 +- openbb_terminal/portfolio/portfolio_helper.py | 12 + openbb_terminal/portfolio/portfolio_model.py | 897 ++++++++++++++---- openbb_terminal/portfolio/portfolio_view.py | 270 ++++++ 4 files changed, 1035 insertions(+), 202 deletions(-) diff --git a/openbb_terminal/portfolio/portfolio_controller.py b/openbb_terminal/portfolio/portfolio_controller.py index b13686946227..0a1b727e5f92 100644 --- a/openbb_terminal/portfolio/portfolio_controller.py +++ b/openbb_terminal/portfolio/portfolio_controller.py @@ -80,6 +80,16 @@ class PortfolioController(BaseController): "rsquare", "skew", "kurtosis", + "gaintopain", + "trackerr", + "information", + "tail", + "commonsense", + "jensens", + "calmar", + "kelly", + "payoff", + "profitfactor", ] PATH = "/portfolio/" @@ -327,6 +337,9 @@ def call_load(self, other_args: List[str]): # Add in the Risk-free rate self.portfolio.add_rf(ns_parser.risk_free_rate) + # Update all period + portfolio_helper.PERIODS_DAYS["all"] = len(self.portfolio.returns) + console.print(f"\n[bold]Portfolio:[/bold] {self.portfolio_name}") console.print(f"[bold]Risk Free Rate:[/bold] {self.portfolio.rf}") @@ -771,10 +784,9 @@ def call_om(self, other_args: List[str]): ns_parser.end, ) else: - if not self.portfolio_name: - console.print( - "[red]Please first define the portfolio (via 'load')[/red]\n" - ) + console.print( + "[red]Please first define the portfolio (via 'load')[/red]\n" + ) @log_start_end(log=logger) def call_cret(self, other_args: List[str]): @@ -1172,6 +1184,44 @@ def call_metric(self, other_args: List[str]): ) elif ns_parser.metric == "rsquare": portfolio_view.display_rsquare(self.portfolio, ns_parser.export) + elif ns_parser.metric == "gaintopain": + portfolio_view.display_gaintopain_ratio( + self.portfolio, ns_parser.export + ) + elif ns_parser.metric == "trackerr": + portfolio_view.display_tracking_error( + self.portfolio, ns_parser.export + ) + elif ns_parser.metric == "information": + portfolio_view.display_information_ratio( + self.portfolio, ns_parser.export + ) + elif ns_parser.metric == "tail": + portfolio_view.display_tail_ratio(self.portfolio, ns_parser.export) + elif ns_parser.metric == "commonsense": + portfolio_view.display_common_sense_ratio( + self.portfolio, ns_parser.export + ) + elif ns_parser.metric == "jensens": + portfolio_view.display_jensens_alpha( + self.portfolio, ns_parser.risk_free_rate, ns_parser.export + ) + elif ns_parser.metric == "calmar": + portfolio_view.display_calmar_ratio( + self.portfolio, ns_parser.export + ) + elif ns_parser.metric == "kelly": + portfolio_view.display_kelly_criterion( + self.portfolio, ns_parser.export + ) + elif ns_parser.metric == "payoff": + portfolio_view.display_payoff_ratio( + self.portfolio, ns_parser.export + ) + elif ns_parser.metric == "profitfactor": + portfolio_view.display_profit_factor( + self.portfolio, ns_parser.export + ) @log_start_end(log=logger) def call_distr(self, other_args: List[str]): diff --git a/openbb_terminal/portfolio/portfolio_helper.py b/openbb_terminal/portfolio/portfolio_helper.py index 8f349fe03209..108f84a1b0a8 100644 --- a/openbb_terminal/portfolio/portfolio_helper.py +++ b/openbb_terminal/portfolio/portfolio_helper.py @@ -113,7 +113,19 @@ PERIODS = ["mtd", "qtd", "ytd", "3m", "6m", "1y", "3y", "5y", "10y", "all"] +now = datetime.now() PERIODS_DAYS = { + "mtd": (now - datetime(now.year, now.month, 1)).days, + "qtd": ( + now + - datetime( + now.year, + 1 if now.month < 4 else 4 if now.month < 7 else 7 if now.month < 7 else 10, + 1, + ) + ).days, + "ytd": (now - datetime(now.year, 1, 1)).days, + "all": 0, "3m": 3 * 21, "6m": 6 * 21, "1y": 12 * 21, diff --git a/openbb_terminal/portfolio/portfolio_model.py b/openbb_terminal/portfolio/portfolio_model.py index db40fca0cf35..1fd492d936b7 100644 --- a/openbb_terminal/portfolio/portfolio_model.py +++ b/openbb_terminal/portfolio/portfolio_model.py @@ -26,8 +26,8 @@ @log_start_end(log=logger) -def get_rolling_beta( - df: pd.DataFrame, hist: pd.DataFrame, mark: pd.DataFrame, n: pd.DataFrame +def get_rolling_beta2( + df: pd.DataFrame, hist: pd.DataFrame, mark: pd.DataFrame, n: pd.DataFrame ) -> pd.DataFrame: """Turns the holdings of a portfolio into a rolling beta dataframe @@ -182,22 +182,586 @@ def calculate_drawdown(input_series: pd.Series, is_returns: bool = False) -> pd. return drawdown -def get_gaintopain_ratio(desired_return: float, tolerable_maximum_draw_down: float): +@log_start_end(log=logger) +def get_gaintopain_ratio(returns: pd.DataFrame, benchmark_returns: pd.DataFrame): """Gets Pain-to-Gain ratio Parameters ---------- - desired_return: float - Desired return - tolerable_maximum_draw_down: float - Maximum tolerable draw down + returns: pd.Series + Series of portfolio returns + benchmark_returns: pd.Series + Series of benchmark returns + + Returns + ------- + pd.DataFrame + DataFrame of the portfolio's gain-to-pain ratio + """ + vals = list() + for period in portfolio_helper.PERIODS: + period_return = portfolio_helper.filter_df_by_period(returns, period) + period_bench_return = portfolio_helper.filter_df_by_period( + benchmark_returns, period + ) + if not period_return.empty: + vals.append( + [ + round( + ( + (1 + period_return.shift(periods=1, fill_value=0)).cumprod() + - 1 + ).iloc[-1] + / portfolio_helper.get_maximum_drawdown(period_return), + 3, + ), + round( + ( + ( + 1 + period_bench_return.shift(periods=1, fill_value=0) + ).cumprod() + - 1 + ).iloc[-1] + / portfolio_helper.get_maximum_drawdown(period_bench_return), + 3, + ), + ] + ) + else: + vals.append(["-", "-"]) + gtr_period_df = pd.DataFrame( + vals, index=portfolio_helper.PERIODS, columns=["Portfolio", "Benchmark"] + ) + + return gtr_period_df + + +@log_start_end(log=logger) +def get_rolling_beta( + returns: pd.Series, benchmark_returns: pd.Series, period: float = 252 +): + """Get rolling beta + + Parameters + ---------- + returns: pd.Series + Series of portfolio returns + benchmark_returns: pd.Series + Series of benchmark returns + period: float + Interval used for rolling values + + Returns + ------- + pd.DataFrame + DataFrame of the portfolio's rolling beta + """ + # Rolling beta is defined as Cov(Port,Bench)/var(Bench) + covs = ( + pd.DataFrame({"Portfolio": returns, "Benchmark": benchmark_returns}) + .dropna(axis=0) + .rolling(max(1, period)) + .cov() + .unstack() + .dropna() + ) + rolling_beta = covs["Portfolio"]["Benchmark"] / covs["Benchmark"]["Benchmark"] + + return rolling_beta + + +@log_start_end(log=logger) +def get_tracking_error( + returns: pd.Series, benchmark_returns: pd.Series, period: float = 252 +): + """Get tracking error + + Parameters + ---------- + returns: pd.Series + Series of portfolio returns + benchmark_returns: pd.Series + Series of benchmark returns + period: float + Interval used for rolling values + + Returns + ------- + pd.DataFrame + DataFrame of tracking errors during different time periods + pd.Series + Series of rolling tracking error + """ + diff_returns = returns - benchmark_returns + + trackr_rolling = diff_returns.rolling(period, min_periods=period).std() + + vals = list() + for period in portfolio_helper.PERIODS: + period_return = portfolio_helper.filter_df_by_period(returns, period) + if not period_return.empty: + vals.append([round(period_return.std(), 3)]) + else: + vals.append(["-"]) + trackr_period_df = pd.DataFrame( + vals, index=portfolio_helper.PERIODS, columns=["Tracking Error"] + ) + + return trackr_period_df, trackr_rolling + + +@log_start_end(log=logger) +def get_information_ratio( + returns: pd.Series, benchmark_returns: pd.Series, period: float = 252 +): + """ + + Parameters + ---------- + returns: pd.Series + Series of portfolio returns + benchmark_returns: pd.Series + Series of benchmark returns + period: float + Interval used for rolling values + + Returns + ------- + pd.DataFrame + DataFrame of the information ratio during different time periods + pd.Series + Series of rolling information ratio + """ + diff_returns = returns - benchmark_returns + _, tracking_err = get_tracking_error(returns, benchmark_returns, period) + + ir_rolling = ( + (1.0 + diff_returns).rolling(window=period).agg(lambda x: x.prod()) - 1 + ) / tracking_err + + vals = list() + for period in portfolio_helper.PERIODS: + period_return = portfolio_helper.filter_df_by_period(returns, period) + period_track_err = portfolio_helper.filter_df_by_period(tracking_err, period) + if not period_return.empty: + vals.append( + [ + round( + ( + (1 + period_return.shift(periods=1, fill_value=0)).cumprod() + - 1 + ).iloc[-1] + / period_track_err.iloc[-1], + 3, + ) + ] + ) + else: + vals.append(["-"]) + + ir_period_df = pd.DataFrame( + vals, index=portfolio_helper.PERIODS, columns=["Information Ratio"] + ) + + return ir_period_df, ir_rolling + + +@log_start_end(log=logger) +def get_tail_ratio( + returns: pd.Series, benchmark_returns: pd.Series, period: float = 252 +): + """ + + Parameters + ---------- + returns: pd.Series + Series of portfolio returns + benchmark_returns: pd.Series + Series of benchmark returns + period: float + Interval used for rolling values + + Returns + ------- + pd.DataFrame + DataFrame of the portfolios and the benchmarks tail ratio during different time periods + pd.Series + Series of the portfolios rolling tail ratio + pd.Series + Series of the benchmarks rolling tail ratio + """ + returns_r = returns.rolling(period, min_periods=period) + benchmark_returns_r = benchmark_returns.rolling(period, min_periods=period) + + portfolio_tr = returns_r.quantile(0.95) / abs(returns_r.quantile(0.05)) + benchmark_tr = benchmark_returns_r.quantile(0.95) / abs( + benchmark_returns_r.quantile(0.05) + ) + + vals = list() + for period in portfolio_helper.PERIODS: + period_return = portfolio_helper.filter_df_by_period(returns, period) + period_bench_return = portfolio_helper.filter_df_by_period( + benchmark_returns, period + ) + if not period_return.empty: + vals.append( + [ + round( + period_return.quantile(0.95) + / abs(period_return.quantile(0.05)), + 3, + ), + round( + period_bench_return.quantile(0.95) + / abs(period_bench_return.quantile(0.05)), + 3, + ), + ] + ) + else: + vals.append(["-", "-"]) + + tailr_period_df = pd.DataFrame( + vals, index=portfolio_helper.PERIODS, columns=["Portfolio", "Benchmark"] + ) + + return tailr_period_df, portfolio_tr, benchmark_tr + + +@log_start_end(log=logger) +def get_common_sense_ratio(returns: pd.Series, benchmark_returns: pd.Series): + """Get common sense ratio + + Parameters + ---------- + returns: pd.Series + Series of portfolio returns + benchmark_returns: pd.Series + Series of benchmark returns + + Returns + ------- + pd.DataFrame + DataFrame of the portfolios and the benchmarks common sense ratio during different time periods + """ + tail_ratio_df, _, _ = get_tail_ratio(returns, benchmark_returns) + + vals = list() + for period in portfolio_helper.PERIODS: + period_return = portfolio_helper.filter_df_by_period(returns, period) + period_bench_return = portfolio_helper.filter_df_by_period( + benchmark_returns, period + ) + if not period_return.empty: + vals.append( + [ + round( + tail_ratio_df.loc[period, "Portfolio"] + * ( + (1 + period_return.shift(periods=1, fill_value=0)).cumprod() + - 1 + ).iloc[-1] + / portfolio_helper.get_maximum_drawdown(period_return), + 3, + ), + round( + tail_ratio_df.loc[period, "Benchmark"] + * ( + ( + 1 + period_bench_return.shift(periods=1, fill_value=0) + ).cumprod() + - 1 + ).iloc[-1] + / portfolio_helper.get_maximum_drawdown(period_bench_return), + 3, + ), + ] + ) + else: + vals.append(["-", "-"]) + + csr_period_df = pd.DataFrame( + vals, index=portfolio_helper.PERIODS, columns=["Portfolio", "Benchmark"] + ) + + return csr_period_df + + +@log_start_end(log=logger) +def get_jensens_alpha( + returns: pd.Series, benchmark_returns: pd.Series, rf: float = 0, period: float = 252 +): + """Get jensen's alpha + + Parameters + ---------- + returns: pd.Series + Series of portfolio returns + benchmark_returns: pd.Series + Series of benchmark returns + rf: float + Risk free rate + period: float + Interval used for rolling values + + Returns + ------- + pd.DataFrame + DataFrame of jensens's alpha during different time periods + pd.Series + Series of jensens's alpha data + """ + periods = portfolio_helper.PERIODS_DAYS + + period_cum_returns = (1.0 + returns).rolling(window=period).agg( + lambda x: x.prod() + ) - 1 + period_cum_bench_returns = (1.0 + benchmark_returns).rolling(window=period).agg( + lambda x: x.prod() + ) - 1 + rfr_cum_returns = rf * period / 252 + beta = get_rolling_beta(returns, benchmark_returns, period) + ja_rolling = period_cum_returns - ( + rfr_cum_returns + beta * (period_cum_bench_returns - rfr_cum_returns) + ) + + vals = list() + for period in portfolio_helper.PERIODS: + period_return = portfolio_helper.filter_df_by_period(returns, period) + period_bench_return = portfolio_helper.filter_df_by_period( + benchmark_returns, period + ) + if not period_return.empty: + beta = get_rolling_beta(returns, benchmark_returns, periods[period]) + if not beta.empty: + beta = beta.iloc[-1] + period_cum_returns = ( + (1 + period_return.shift(periods=1, fill_value=0)).cumprod() - 1 + ).iloc[-1] + period_cum_bench_returns = ( + (1 + period_bench_return.shift(periods=1, fill_value=0)).cumprod() + - 1 + ).iloc[-1] + rfr_cum_returns = rf * periods[period] / 252 + vals.append( + [ + round( + period_cum_returns + - ( + rfr_cum_returns + + beta * (period_cum_bench_returns - rfr_cum_returns) + ), + 3, + ) + ] + ) + else: + vals.append(["-"]) + else: + vals.append(["-"]) + + ja_period_df = pd.DataFrame( + vals, index=portfolio_helper.PERIODS, columns=["Portfolio"] + ) + + return ja_period_df, ja_rolling + + +@log_start_end(log=logger) +def get_calmar_ratio( + returns: pd.Series, benchmark_returns: pd.Series, period: float = 756 +): + """Get calmar ratio + + Parameters + ---------- + returns: pd.Series + Series of portfolio returns + benchmark_returns: pd.Series + Series of benchmark returns + period: float + Interval used for rolling values + + Returns + ------- + pd.DataFrame + DataFrame of calmar ratio of the benchmark and portfolio during different time periods + pd.Series + Series of calmar ratio data + """ + periods = portfolio_helper.PERIODS_DAYS + + period_cum_returns = (1.0 + returns).rolling(window=period).agg( + lambda x: x.prod() + ) - 1 + + # Calculate annual return + annual_return = period_cum_returns ** (1 / (period / 252)) - 1 + + cr_rolling = annual_return / portfolio_helper.get_maximum_drawdown(returns) + + vals = list() + for period in portfolio_helper.PERIODS: + period_return = portfolio_helper.filter_df_by_period(returns, period) + period_bench_return = portfolio_helper.filter_df_by_period( + benchmark_returns, period + ) + if (not period_return.empty) and (periods[period] != 0): + period_cum_returns = ( + (1 + period_return.shift(periods=1, fill_value=0)).cumprod() - 1 + ).iloc[-1] + period_cum_bench_returns = ( + (1 + period_bench_return.shift(periods=1, fill_value=0)).cumprod() - 1 + ).iloc[-1] + annual_return = period_cum_returns ** (1 / (periods[period] / 252)) - 1 + annual_bench_return = ( + period_cum_bench_returns ** (1 / (periods[period] / 252)) - 1 + ) + drawdown = portfolio_helper.get_maximum_drawdown(period_return) + bench_drawdown = portfolio_helper.get_maximum_drawdown(period_bench_return) + if (drawdown != 0) and (bench_drawdown != 0): + vals.append( + [ + round(annual_return / drawdown, 3), + round(annual_bench_return / bench_drawdown, 3), + ] + ) + else: + vals.append(["-", "-"]) + else: + vals.append(["-", "-"]) + + cr_period_df = pd.DataFrame( + vals, index=portfolio_helper.PERIODS, columns=["Portfolio", "Benchmark"] + ) + + return cr_period_df, cr_rolling + + +@log_start_end(log=logger) +def get_kelly_criterion(returns: pd.Series, portfolio_trades: pd.DataFrame): + """Gets kelly criterion + + Parameters + ---------- + returns: pd.Series + Series of portfolio returns + portfolio_trades: pd.DataFrame + DataFrame of the portfolio trades with trade return in % + + Returns + ------- + pd.DataFrame + DataFrame of kelly criterion of the portfolio during different time periods + """ + portfolio_trades["Date"] = pd.to_datetime(portfolio_trades["Date"]) + portfolio_trades = portfolio_trades.set_index("Date") + + vals = list() + for period in portfolio_helper.PERIODS: + period_return = portfolio_helper.filter_df_by_period(returns, period) + period_portfolio_tr = portfolio_helper.filter_df_by_period( + portfolio_trades, period + ) + if (not period_return.empty) and (not period_portfolio_tr.empty): + w = len(period_return[period_return > 0]) / len(period_return) + r = len( + period_portfolio_tr[period_portfolio_tr["% Portfolio Return"] > 0] + ) / len(period_portfolio_tr) + vals.append([round(w - (1 - w) / r, 3)]) + else: + vals.append(["-"]) + + kc_period_df = pd.DataFrame( + vals, index=portfolio_helper.PERIODS, columns=["Kelly %"] + ) + + return kc_period_df + + +@log_start_end(log=logger) +def get_payoff_ratio(portfolio_trades: pd.DataFrame): + """Gets payoff ratio + + Parameters + ---------- + portfolio_trades: pd.DataFrame + DataFrame of the portfolio trades with trade return in % and abs values + + Returns + ------- + pd.DataFrame + DataFrame of payoff ratio of the portfolio during different time periods + """ + portfolio_trades["Date"] = pd.to_datetime(portfolio_trades["Date"]) + portfolio_trades = portfolio_trades.set_index("Date") + + vals = list() + for period in portfolio_helper.PERIODS: + period_portfolio_tr = portfolio_helper.filter_df_by_period( + portfolio_trades, period + ) + if not portfolio_trades.empty: + portfolio_wins = period_portfolio_tr[ + period_portfolio_tr["% Portfolio Return"] > 0 + ] + portfolio_loses = period_portfolio_tr[ + period_portfolio_tr["% Portfolio Return"] < 0 + ] + avg_w = portfolio_wins["Abs Portfolio Return"].mean() + avg_l = portfolio_loses["Abs Portfolio Return"].mean() + vals.append([round(avg_w / avg_l, 3)]) + else: + vals.append(["-"]) + + pr_period_ratio = pd.DataFrame( + vals, index=portfolio_helper.PERIODS, columns=["Payoff Ratio"] + ) + + return pr_period_ratio + + +@log_start_end(log=logger) +def get_profit_factor(portfolio_trades: pd.DataFrame): + """Gets profit factor + + Parameters + ---------- + portfolio_trades: pd.DataFrame + DataFrame of the portfolio trades with trade return in % and abs values Returns ------- - float - Pain-to-Gain ratio + pd.DataFrame + DataFrame of profit factor of the portfolio during different time periods """ - return desired_return / tolerable_maximum_draw_down + portfolio_trades["Date"] = pd.to_datetime(portfolio_trades["Date"]) + portfolio_trades = portfolio_trades.set_index("Date") + + vals = list() + for period in portfolio_helper.PERIODS: + period_portfolio_tr = portfolio_helper.filter_df_by_period( + portfolio_trades, period + ) + if not portfolio_trades.empty: + portfolio_wins = period_portfolio_tr[ + period_portfolio_tr["% Portfolio Return"] > 0 + ] + portfolio_loses = period_portfolio_tr[ + period_portfolio_tr["% Portfolio Return"] < 0 + ] + gross_profit = portfolio_wins["Abs Portfolio Return"].sum() + gross_loss = portfolio_loses["Abs Portfolio Return"].sum() + vals.append([round(gross_profit / gross_loss, 3)]) + else: + vals.append(["-"]) + + pf_period_df = pd.DataFrame( + vals, index=portfolio_helper.PERIODS, columns=["Profit Factor"] + ) + + return pf_period_df class Portfolio: @@ -366,8 +930,8 @@ def generate_holdings_from_trades(self, yfinance_use_close: bool = False): portfolio[ pd.MultiIndex.from_product([["StockHoldings"], self._stock_tickers]) ] = ( - portfolio["Quantity"][self._stock_tickers] - * portfolio["Close"][self._stock_tickers] + portfolio["Quantity"][self._stock_tickers] + * portfolio["Close"][self._stock_tickers] ) else: portfolio[pd.MultiIndex.from_product([["StockHoldings"], ["temp"]])] = 0 @@ -377,8 +941,8 @@ def generate_holdings_from_trades(self, yfinance_use_close: bool = False): portfolio[ pd.MultiIndex.from_product([["ETFHoldings"], self._etf_tickers]) ] = ( - portfolio["Quantity"][self._etf_tickers] - * portfolio["Close"][self._etf_tickers] + portfolio["Quantity"][self._etf_tickers] + * portfolio["Close"][self._etf_tickers] ) else: portfolio[pd.MultiIndex.from_product([["ETFHoldings"], ["temp"]])] = 0 @@ -387,8 +951,8 @@ def generate_holdings_from_trades(self, yfinance_use_close: bool = False): portfolio[ pd.MultiIndex.from_product([["CryptoHoldings"], self._crypto_tickers]) ] = ( - portfolio["Quantity"][self._crypto_tickers] - * portfolio["Close"][self._crypto_tickers] + portfolio["Quantity"][self._crypto_tickers] + * portfolio["Close"][self._crypto_tickers] ) else: portfolio[pd.MultiIndex.from_product([["CryptoHoldings"], ["temp"]])] = 0 @@ -398,11 +962,11 @@ def generate_holdings_from_trades(self, yfinance_use_close: bool = False): # stocks bought + stocks sold if "CASH" not in portfolio["Investment"]: portfolio["CashHold"] = ( - portfolio["Investment"][ - self._stock_tickers + self._etf_tickers + self._crypto_tickers - ].sum(axis=1) - + portfolio["Fees"].sum(axis=1) - + portfolio["Premium"].sum(axis=1) + portfolio["Investment"][ + self._stock_tickers + self._etf_tickers + self._crypto_tickers + ].sum(axis=1) + + portfolio["Fees"].sum(axis=1) + + portfolio["Premium"].sum(axis=1) ) else: portfolio["CashHold"] = portfolio["Investment"]["CASH"] - portfolio[ @@ -413,17 +977,17 @@ def generate_holdings_from_trades(self, yfinance_use_close: bool = False): # Subtract Fees or Premiums from cash holdings portfolio["CashHold"] = ( - portfolio["CashHold"] - - portfolio["Fees"].sum(axis=1) - - portfolio["Premium"].sum(axis=1) + portfolio["CashHold"] + - portfolio["Fees"].sum(axis=1) + - portfolio["Premium"].sum(axis=1) ) portfolio["CashHold"] = portfolio["CashHold"].cumsum() portfolio["TotalHoldings"] = ( - portfolio["CashHold"] - + portfolio["StockHoldings"].sum(axis=1) - + portfolio["ETFHoldings"].sum(axis=1) - + portfolio["CryptoHoldings"].sum(axis=1) + portfolio["CashHold"] + + portfolio["StockHoldings"].sum(axis=1) + + portfolio["ETFHoldings"].sum(axis=1) + + portfolio["CryptoHoldings"].sum(axis=1) ) self.portfolio_value = portfolio["TotalHoldings"] @@ -462,17 +1026,15 @@ def generate_holdings_from_trades(self, yfinance_use_close: bool = False): "Investment" ] self.portfolio_trades["Portfolio Value"][index] = ( - self.portfolio_trades["Close"][index] * trade["Quantity"] + self.portfolio_trades["Close"][index] * trade["Quantity"] ) self.portfolio_trades["% Portfolio Return"][index] = ( - self.portfolio_trades["Portfolio Value"][ - index] - / self.portfolio_trades[ - "Portfolio Investment"][index] - ) - 1 + self.portfolio_trades["Portfolio Value"][index] + / self.portfolio_trades["Portfolio Investment"][index] + ) - 1 self.portfolio_trades["Abs Portfolio Return"].loc[index] = ( - self.portfolio_trades["Portfolio Value"][index] - - self.portfolio_trades["Portfolio Investment"][index] + self.portfolio_trades["Portfolio Value"][index] + - self.portfolio_trades["Portfolio Investment"][index] ) self.portfolio = portfolio.copy() @@ -514,7 +1076,7 @@ def get_yahoo_close_prices(self, use_close: bool = False): @log_start_end(log=logger) def get_crypto_yfinance(self): - """Gets historical coin data from coingecko""" + """Gets historical coin data from yfinance""" if self._crypto_tickers: self._historical_crypto = yf.download( self._crypto_tickers, start=self._start_date, progress=False @@ -582,7 +1144,7 @@ def mimic_portfolio_trades_for_benchmark(self, full_shares: bool = False): if not full_shares: self.benchmark_trades["Benchmark Quantity"][index] = ( - trade["Investment"] / self.benchmark_trades["Price"][index] + trade["Investment"] / self.benchmark_trades["Price"][index] ) else: self.benchmark_trades["Benchmark Quantity"][index] = np.floor( @@ -590,22 +1152,20 @@ def mimic_portfolio_trades_for_benchmark(self, full_shares: bool = False): ) self.benchmark_trades["Benchmark Investment"][index] = ( - self.benchmark_trades["Price"][index] - * self.benchmark_trades["Benchmark Quantity"][index] + self.benchmark_trades["Price"][index] + * self.benchmark_trades["Benchmark Quantity"][index] ) self.benchmark_trades["Benchmark Value"][index] = ( - self.benchmark_trades["Close"][index] - * self.benchmark_trades["Benchmark Quantity"][index] + self.benchmark_trades["Close"][index] + * self.benchmark_trades["Benchmark Quantity"][index] ) self.benchmark_trades["% Benchmark Return"][index] = ( - self.benchmark_trades["Benchmark Value"][ - index] - / self.benchmark_trades[ - "Benchmark Investment"][index] - ) - 1 + self.benchmark_trades["Benchmark Value"][index] + / self.benchmark_trades["Benchmark Investment"][index] + ) - 1 self.benchmark_trades["Abs Benchmark Return"][index] = ( - self.benchmark_trades["Benchmark Value"][index] - - self.benchmark_trades["Benchmark Investment"][index] + self.benchmark_trades["Benchmark Value"][index] + - self.benchmark_trades["Benchmark Investment"][index] ) # pylint:disable=no-member @@ -802,9 +1362,9 @@ def get_stats(self, period: str = "all") -> pd.DataFrame: """ df = ( portfolio_helper.filter_df_by_period(self.returns, period) - .describe() - .to_frame() - .join( + .describe() + .to_frame() + .join( portfolio_helper.filter_df_by_period( self.benchmark_returns, period ).describe() @@ -959,6 +1519,19 @@ def get_maximum_drawdown_ratio(self) -> pd.DataFrame: vals, index=portfolio_helper.PERIODS, columns=["Portfolio", "Benchmark"] ) + @log_start_end(log=logger) + def get_gaintopain_ratio(self): + """Gets Pain-to-Gain ratio based on historical data + + Returns + ------- + pd.DataFrame + DataFrame of the portfolio's gain-to-pain ratio + """ + gtp_period_df = get_gaintopain_ratio(self.returns, self.benchmark_returns) + + return gtp_period_df + @log_start_end(log=logger) def get_rolling_beta(self, period: float = 252): """Get rolling beta @@ -973,17 +1546,7 @@ def get_rolling_beta(self, period: float = 252): pd.DataFrame DataFrame of the portfolio's rolling beta """ - - # Rolling beta is defined as Cov(Port,Bench)/var(Bench) - covs = ( - pd.DataFrame({"Portfolio": self.returns, "Benchmark": self.benchmark_returns}) - .dropna(axis=0) - .rolling(period) - .cov() - .unstack() - .dropna() - ) - rolling_beta = covs["Portfolio"]["Benchmark"] / covs["Benchmark"]["Benchmark"] + rolling_beta = get_rolling_beta(self.returns, self.benchmark_returns, period) return rolling_beta @@ -1003,21 +1566,11 @@ def get_tracking_error(self, period: float = 252): pd.Series Series of rolling tracking error """ - diff_returns = self.returns - self.benchmark_returns - - vals = list() - for period in portfolio_helper.PERIODS: - vals.append( - [ - round( - portfolio_helper.filter_df_by_period(self.returns, period).std(), - 3, - ) - ] - ) - trackr_period_df = pd.DataFrame(vals, index=portfolio_helper.PERIODS, columns=["Tracking Error"]) + trackr_period_df, trackr_rolling = get_tracking_error( + self.returns, self.benchmark_returns, period + ) - return trackr_period_df, diff_returns.rolling(period, min_periods=period).std() + return trackr_period_df, trackr_rolling @log_start_end(log=logger) def get_information_ratio(self, period: float = 252): @@ -1035,24 +1588,9 @@ def get_information_ratio(self, period: float = 252): pd.Series Series of rolling information ratio """ - diff_returns = self.returns - self.benchmark_returns - - _, tracking_err = self.get_tracking_error(period=period) - - vals = list() - for period in portfolio_helper.PERIODS: - vals.append( - [ - round( - portfolio_helper.filter_df_by_period(diff_returns, period) / - portfolio_helper.filter_df_by_period(tracking_err, period), - 3, - ) - ] - ) - - ir_period_df = pd.DataFrame(vals, index=portfolio_helper.PERIODS, columns=["Information Ratio"]) - ir_rolling = ((1 + diff_returns.rolling(period, min_periods=period).shift(periods=1, fill_value=0)).cumprod() - 1) / tracking_err + ir_period_df, ir_rolling = get_information_ratio( + self.returns, self.benchmark_returns, period + ) return ir_period_df, ir_rolling @@ -1074,72 +1612,35 @@ def get_tail_ratio(self, period: float = 252): pd.Series Series of the benchmarks rolling tail ratio """ - returns = self.returns.rolling(period, min_periods=period) - benchmark_returns = self.benchmark_returns.rolling(period, min_periods=period) - - portfolio_tr = returns.quantile(0.95) / returns.quantile(0.05) - benchmark_tr = benchmark_returns.quantile(0.95) / benchmark_returns.quantile(0.05) - - vals = list() - for period in portfolio_helper.PERIODS: - vals.append( - [ - round( - portfolio_helper.filter_df_by_period(self.returns, period).quantile(0.95) / - portfolio_helper.filter_df_by_period(self.returns, period).quantile(0.05), - 3, - ), - round( - portfolio_helper.filter_df_by_period(self.benchmark_returns, period).quantile(0.95) / - portfolio_helper.filter_df_by_period(self.benchmark_returns, period).quantile(0.05), - 3, - ), - ] - ) - - tailr_period_df = pd.DataFrame(vals, index=portfolio_helper.PERIODS, columns=["Portfolio", "Benchmark"]) + tailr_period_df, portfolio_tr, benchmark_tr = get_tail_ratio( + self.returns, self.benchmark_returns, period + ) return tailr_period_df, portfolio_tr, benchmark_tr @log_start_end(log=logger) - def get_common_sense_ratio(self, period: float = 252): - tail_ratio_df, portfolio_tr, benchmark_tr = self.get_tail_ratio(period) - - vals = list() - for period in portfolio_helper.PERIODS: - period_return = portfolio_helper.filter_df_by_period(self.returns, period) - period_bench_return = portfolio_helper.filter_df_by_period(self.benchmark_returns, period) - vals.append( - [ - round( - tail_ratio_df.loc[period, "Portfolio"] * - get_gaintopain_ratio( - ((1 + period_return.shift(periods=1, fill_value=0)).cumprod() - 1).iloc[-1], - portfolio_helper.get_maximum_drawdown(period_return)), - 3, - ), - round( - tail_ratio_df.loc[period, "Benchmark"] * - get_gaintopain_ratio( - ((1 + period_bench_return.shift(periods=1, fill_value=0)).cumprod() - 1).iloc[-1], - portfolio_helper.get_maximum_drawdown(period_bench_return)), - 3, - ), - ] - ) + def get_common_sense_ratio(self): + """Get common sense ratio - csr_period_df = pd.DataFrame(vals, index=portfolio_helper.PERIODS, columns=["Portfolio", "Benchmark"]) + Returns + ------- + pd.DataFrame + DataFrame of the portfolios and the benchmarks common sense ratio during different time periods + """ + csr_period_df = get_common_sense_ratio(self.returns, self.benchmark_returns) return csr_period_df @log_start_end(log=logger) - def get_jensens_alpha(self, period: float = 252): + def get_jensens_alpha(self, rf: float = 0, period: float = 252): """Get jensen's alpha Parameters ---------- period: float Interval used for rolling values + rf: float + Risk free rate Returns ------- @@ -1148,69 +1649,69 @@ def get_jensens_alpha(self, period: float = 252): pd.Series Series of jensens's alpha data """ - period_cum_returns = ((1 + self.returns.rolling(period, min_periods=period) - .shift(periods=1, fill_value=0)).cumprod() - 1) - period_cum_bench_returns = ((1 + self.benchmark_returns.rolling(period, min_periods=period) - .shift(periods=1, fill_value=0)).cumprod() - 1) - rfr_cum_returns = self.rf * period / 252 - beta = self.get_rolling_beta(period) - - ja_rolling = period_cum_returns - (rfr_cum_returns + beta * (period_cum_bench_returns - rfr_cum_returns)) - - vals = list() - for period in portfolio_helper.PERIODS: - period_return = portfolio_helper.filter_df_by_period(self.returns, period) - period_bench_return = portfolio_helper.filter_df_by_period(self.benchmark_returns, period) - period_cum_returns = ((1 + period_return.shift(periods=1, fill_value=0)).cumprod() - 1) - period_cum_bench_returns = ((1 + period_bench_return.shift(periods=1, fill_value=0)).cumprod() - 1) - rfr_cum_returns = self.rf * portfolio_helper.PERIODS_DAYS[period] / 252 - beta = self.get_rolling_beta(portfolio_helper.PERIODS_DAYS[period]).iloc[-1, 0] - vals.append( - [ - round( - period_cum_returns - (rfr_cum_returns + beta * (period_cum_bench_returns - rfr_cum_returns)), - 3, - ) - ] - ) - - ja_period_df = pd.DataFrame(vals, index=portfolio_helper.PERIODS, columns=["Portfolio"]) + ja_period_df, ja_rolling = get_jensens_alpha( + self.returns, self.benchmark_returns, rf, period + ) return ja_period_df, ja_rolling @log_start_end(log=logger) def get_calmar_ratio(self, period: float = 756): - period_return = self.returns.rolling(period, min_periods=period) - period_cum_returns = ((1 + period_return.shift(periods=1, fill_value=0)).cumprod() - 1) + """Get calmar ratio - # Calculate annual return - annual_return = (period_cum_returns + 1) ** (1 / (period / 252)) - 1 + Parameters + ---------- + period: float + Interval used for rolling values - cr_rolling = annual_return / portfolio_helper.get_maximum_drawdown(period_return) + Returns + ------- + pd.DataFrame + DataFrame of calmar ratio of the benchmark and portfolio during different time periods + pd.Series + Series of calmar ratio data + """ + cr_period_df, cr_rolling = get_calmar_ratio( + self.returns, self.benchmark_returns, period + ) - vals = list() - for period in portfolio_helper.PERIODS: - period_return = portfolio_helper.filter_df_by_period(self.returns, period) - period_bench_return = portfolio_helper.filter_df_by_period(self.benchmark_returns, period) - annual_return = (period_cum_returns + 1) ** (1 / (period / 252)) - 1 - annual_bench_return = (period_cum_returns + 1) ** (1 / (period / 252)) - 1 - vals.append( - [ - round( - annual_return / portfolio_helper.get_maximum_drawdown(period_return), - 3, - ), - round( - annual_bench_return / portfolio_helper.get_maximum_drawdown(period_bench_return), - 3, - ), - ] - ) + return cr_period_df, cr_rolling - cr_period_df = pd.DataFrame(vals, index=portfolio_helper.PERIODS, columns=["Portfolio", "Benchmark"]) + @log_start_end(log=logger) + def get_kelly_criterion(self): + """Gets kelly criterion - return cr_period_df, cr_rolling + Returns + ------- + pd.DataFrame + DataFrame of kelly criterion of the portfolio during different time periods + """ + kc_period_df = get_kelly_criterion(self.returns, self.portfolio_trades) + + return kc_period_df + + @log_start_end(log=logger) + def get_payoff_ratio(self): + """Gets payoff ratio + Returns + ------- + pd.DataFrame + DataFrame of payoff ratio of the portfolio during different time periods + """ + pr_period_ratio = get_payoff_ratio(self.portfolio_trades) + return pr_period_ratio + @log_start_end(log=logger) + def get_profit_factor(self): + """Gets profit factor + + Returns + ------- + pd.DataFrame + DataFrame of profit factor of the portfolio during different time periods + """ + pf_period_df = get_profit_factor(self.portfolio_trades) + return pf_period_df diff --git a/openbb_terminal/portfolio/portfolio_view.py b/openbb_terminal/portfolio/portfolio_view.py index dc38b4f5110c..597746aae644 100644 --- a/openbb_terminal/portfolio/portfolio_view.py +++ b/openbb_terminal/portfolio/portfolio_view.py @@ -1509,6 +1509,276 @@ def display_maximum_drawdown_ratio( ) +@log_start_end(log=logger) +def display_gaintopain_ratio( + portfolio: portfolio_model.Portfolio, + export: str = "", +): + """Display gain-to-pain ratio for multiple periods + + Parameters + ---------- + portfolio: Portfolio + Portfolio object with returns and benchmark loaded + export : str + Export data format + """ + df = portfolio.get_gaintopain_ratio() + print_rich_table( + df, + title="Gain-to-pain ratio for portfolio and benchmark", + show_index=True, + floatfmt=".3f", + ) + export_data( + export, + os.path.dirname(os.path.abspath(__file__)), + "metric_gaintopain_ratio", + df, + ) + + +@log_start_end(log=logger) +def display_tracking_error( + portfolio: portfolio_model.Portfolio, + export: str = "", +): + """Display tracking error for multiple periods + + Parameters + ---------- + portfolio: Portfolio + Portfolio object with returns and benchmark loaded + export : str + Export data format + """ + df, _ = portfolio.get_tracking_error() + print_rich_table( + df, + title="Benchmark Tracking Error", + show_index=True, + floatfmt=".3f", + ) + export_data( + export, os.path.dirname(os.path.abspath(__file__)), "metric_tracking_error", df + ) + + +@log_start_end(log=logger) +def display_information_ratio( + portfolio: portfolio_model.Portfolio, + export: str = "", +): + """Display information ratio for multiple periods + + Parameters + ---------- + portfolio: Portfolio + Portfolio object with returns and benchmark loaded + export : str + Export data format + """ + df, _ = portfolio.get_information_ratio() + print_rich_table( + df, + title="Information ratio for portfolio", + show_index=True, + floatfmt=".3f", + ) + export_data( + export, + os.path.dirname(os.path.abspath(__file__)), + "metric_information_ratio", + df, + ) + + +@log_start_end(log=logger) +def display_tail_ratio( + portfolio: portfolio_model.Portfolio, + export: str = "", +): + """Display tail ratio for multiple periods + + Parameters + ---------- + portfolio: Portfolio + Portfolio object with returns and benchmark loaded + export : str + Export data format + """ + df, _, _ = portfolio.get_tail_ratio() + print_rich_table( + df, + title="Tail ratio for portfolio and benchmark", + show_index=True, + floatfmt=".3f", + ) + export_data( + export, os.path.dirname(os.path.abspath(__file__)), "metric_tail_ratio", df + ) + + +@log_start_end(log=logger) +def display_common_sense_ratio( + portfolio: portfolio_model.Portfolio, + export: str = "", +): + """Display common sense ratio for multiple periods + + Parameters + ---------- + portfolio: Portfolio + Portfolio object with returns and benchmark loaded + export : str + Export data format + """ + df = portfolio.get_common_sense_ratio() + print_rich_table( + df, + title="Common sense ratio for portfolio and benchmark", + show_index=True, + floatfmt=".3f", + ) + export_data( + export, + os.path.dirname(os.path.abspath(__file__)), + "metric_common_sense_ratio", + df, + ) + + +@log_start_end(log=logger) +def display_jensens_alpha( + portfolio: portfolio_model.Portfolio, + rf: float = 0, + export: str = "", +): + """Display jensens alpha for multiple periods + + Parameters + ---------- + portfolio: Portfolio + Portfolio object with returns and benchmark loaded + rf: float + Risk free rate + export : str + Export data format + """ + df, _ = portfolio.get_jensens_alpha(rf=rf) + print_rich_table( + df, + title="Portfolio's jensen's alpha", + show_index=True, + floatfmt=".3f", + ) + export_data( + export, os.path.dirname(os.path.abspath(__file__)), "metric_jensens_alpha", df + ) + + +@log_start_end(log=logger) +def display_calmar_ratio( + portfolio: portfolio_model.Portfolio, + export: str = "", +): + """Display calmar ratio for multiple periods + + Parameters + ---------- + portfolio: Portfolio + Portfolio object with returns and benchmark loaded + export : str + Export data format + """ + df, _ = portfolio.get_calmar_ratio() + print_rich_table( + df, + title="Calmar ratio for portfolio and benchmark", + show_index=True, + floatfmt=".3f", + ) + export_data( + export, os.path.dirname(os.path.abspath(__file__)), "metric_calmar_ratio", df + ) + + +@log_start_end(log=logger) +def display_kelly_criterion( + portfolio: portfolio_model.Portfolio, + export: str = "", +): + """Display kelly criterion for multiple periods + + Parameters + ---------- + portfolio: Portfolio + Portfolio object with trades and returns loaded + export : str + Export data format + """ + df = portfolio.get_kelly_criterion() + print_rich_table( + df, + title="Kelly criterion of the portfolio", + show_index=True, + floatfmt=".3f", + ) + export_data( + export, os.path.dirname(os.path.abspath(__file__)), "metric_kelly_criterion", df + ) + + +def display_payoff_ratio( + portfolio: portfolio_model.Portfolio, + export: str = "", +): + """Display payoff ratio for multiple periods + + Parameters + ---------- + portfolio: Portfolio + Portfolio object with trades loaded + export : str + Export data format + """ + df = portfolio.get_payoff_ratio() + print_rich_table( + df, + title="Portfolio's payoff ratio", + show_index=True, + floatfmt=".3f", + ) + export_data( + export, os.path.dirname(os.path.abspath(__file__)), "metric_payoff_ratio", df + ) + + +def display_profit_factor( + portfolio: portfolio_model.Portfolio, + export: str = "", +): + """Display profit factor for multiple periods + + Parameters + ---------- + portfolio: Portfolio + Portfolio object with trades loaded + export : str + Export data format + """ + df = portfolio.get_profit_factor() + print_rich_table( + df, + title="Portfolio's profit factor", + show_index=True, + floatfmt=".3f", + ) + export_data( + export, os.path.dirname(os.path.abspath(__file__)), "metric_profit_factor", df + ) + + @log_start_end(log=logger) def display_summary_portfolio_benchmark( portfolio_returns: pd.Series, From b98c8a1ea341cf0acfc4ee4ab69c0c0241aeabc3 Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Sat, 2 Jul 2022 10:19:19 +0200 Subject: [PATCH 11/24] Linting --- openbb_terminal/portfolio/portfolio_model.py | 44 ++++++++++---------- 1 file changed, 22 insertions(+), 22 deletions(-) diff --git a/openbb_terminal/portfolio/portfolio_model.py b/openbb_terminal/portfolio/portfolio_model.py index 1fd492d936b7..431990b87dff 100644 --- a/openbb_terminal/portfolio/portfolio_model.py +++ b/openbb_terminal/portfolio/portfolio_model.py @@ -297,8 +297,8 @@ def get_tracking_error( trackr_rolling = diff_returns.rolling(period, min_periods=period).std() vals = list() - for period in portfolio_helper.PERIODS: - period_return = portfolio_helper.filter_df_by_period(returns, period) + for periods in portfolio_helper.PERIODS: + period_return = portfolio_helper.filter_df_by_period(returns, periods) if not period_return.empty: vals.append([round(period_return.std(), 3)]) else: @@ -340,9 +340,9 @@ def get_information_ratio( ) / tracking_err vals = list() - for period in portfolio_helper.PERIODS: - period_return = portfolio_helper.filter_df_by_period(returns, period) - period_track_err = portfolio_helper.filter_df_by_period(tracking_err, period) + for periods in portfolio_helper.PERIODS: + period_return = portfolio_helper.filter_df_by_period(returns, periods) + period_track_err = portfolio_helper.filter_df_by_period(tracking_err, periods) if not period_return.empty: vals.append( [ @@ -399,10 +399,10 @@ def get_tail_ratio( ) vals = list() - for period in portfolio_helper.PERIODS: - period_return = portfolio_helper.filter_df_by_period(returns, period) + for periods in portfolio_helper.PERIODS: + period_return = portfolio_helper.filter_df_by_period(returns, periods) period_bench_return = portfolio_helper.filter_df_by_period( - benchmark_returns, period + benchmark_returns, periods ) if not period_return.empty: vals.append( @@ -512,7 +512,7 @@ def get_jensens_alpha( pd.Series Series of jensens's alpha data """ - periods = portfolio_helper.PERIODS_DAYS + periods_d = portfolio_helper.PERIODS_DAYS period_cum_returns = (1.0 + returns).rolling(window=period).agg( lambda x: x.prod() @@ -527,13 +527,13 @@ def get_jensens_alpha( ) vals = list() - for period in portfolio_helper.PERIODS: - period_return = portfolio_helper.filter_df_by_period(returns, period) + for periods in portfolio_helper.PERIODS: + period_return = portfolio_helper.filter_df_by_period(returns, periods) period_bench_return = portfolio_helper.filter_df_by_period( - benchmark_returns, period + benchmark_returns, periods ) if not period_return.empty: - beta = get_rolling_beta(returns, benchmark_returns, periods[period]) + beta = get_rolling_beta(returns, benchmark_returns, periods_d[periods]) if not beta.empty: beta = beta.iloc[-1] period_cum_returns = ( @@ -543,7 +543,7 @@ def get_jensens_alpha( (1 + period_bench_return.shift(periods=1, fill_value=0)).cumprod() - 1 ).iloc[-1] - rfr_cum_returns = rf * periods[period] / 252 + rfr_cum_returns = rf * periods_d[periods] / 252 vals.append( [ round( @@ -590,7 +590,7 @@ def get_calmar_ratio( pd.Series Series of calmar ratio data """ - periods = portfolio_helper.PERIODS_DAYS + periods_d = portfolio_helper.PERIODS_DAYS period_cum_returns = (1.0 + returns).rolling(window=period).agg( lambda x: x.prod() @@ -602,21 +602,21 @@ def get_calmar_ratio( cr_rolling = annual_return / portfolio_helper.get_maximum_drawdown(returns) vals = list() - for period in portfolio_helper.PERIODS: - period_return = portfolio_helper.filter_df_by_period(returns, period) + for periods in portfolio_helper.PERIODS: + period_return = portfolio_helper.filter_df_by_period(returns, periods) period_bench_return = portfolio_helper.filter_df_by_period( - benchmark_returns, period + benchmark_returns, periods ) - if (not period_return.empty) and (periods[period] != 0): + if (not period_return.empty) and (periods_d[periods] != 0): period_cum_returns = ( (1 + period_return.shift(periods=1, fill_value=0)).cumprod() - 1 ).iloc[-1] period_cum_bench_returns = ( (1 + period_bench_return.shift(periods=1, fill_value=0)).cumprod() - 1 ).iloc[-1] - annual_return = period_cum_returns ** (1 / (periods[period] / 252)) - 1 + annual_return = period_cum_returns ** (1 / (periods_d[periods] / 252)) - 1 annual_bench_return = ( - period_cum_bench_returns ** (1 / (periods[period] / 252)) - 1 + period_cum_bench_returns ** (1 / (periods_d[periods] / 252)) - 1 ) drawdown = portfolio_helper.get_maximum_drawdown(period_return) bench_drawdown = portfolio_helper.get_maximum_drawdown(period_bench_return) @@ -658,7 +658,7 @@ def get_kelly_criterion(returns: pd.Series, portfolio_trades: pd.DataFrame): portfolio_trades["Date"] = pd.to_datetime(portfolio_trades["Date"]) portfolio_trades = portfolio_trades.set_index("Date") - vals = list() + vals: list = list() for period in portfolio_helper.PERIODS: period_return = portfolio_helper.filter_df_by_period(returns, period) period_portfolio_tr = portfolio_helper.filter_df_by_period( From 6ba454dfea8495d7cc00867752e940398b1ad2d9 Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Sat, 2 Jul 2022 10:35:10 +0200 Subject: [PATCH 12/24] Linting --- openbb_terminal/portfolio/portfolio_model.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/openbb_terminal/portfolio/portfolio_model.py b/openbb_terminal/portfolio/portfolio_model.py index 431990b87dff..433c362c54b0 100644 --- a/openbb_terminal/portfolio/portfolio_model.py +++ b/openbb_terminal/portfolio/portfolio_model.py @@ -17,7 +17,7 @@ from openbb_terminal.portfolio import portfolio_helper, allocation_model from openbb_terminal.rich_config import console -# pylint: disable=E1136,W0201,R0902 +# pylint: disable=E1136,W0201,R0902,C0302 # pylint: disable=unsupported-assignment-operation logger = logging.getLogger(__name__) cg = CoinGeckoAPI() @@ -801,10 +801,10 @@ def __init__(self, trades: pd.DataFrame = pd.DataFrame(), rf: float = 0.0): self.benchmark: pd.DataFrame = pd.DataFrame() self._historical_crypto: pd.DataFrame = pd.DataFrame() self._historical_prices: pd.DataFrame = pd.DataFrame() - self.returns = None + self.returns: pd.Series = pd.Series() self.portfolio_value = None self.ItemizedHoldings = None - self.benchmark_returns = None + self.benchmark_returns: pd.Series = pd.Series() self.portfolio_sectors_allocation = pd.DataFrame() self.portfolio_assets_allocation = pd.DataFrame() self.benchmark_sectors_allocation = pd.DataFrame() From a1b5cca3205b56d4ef86abf761ef616f17b9c42f Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Sat, 2 Jul 2022 10:48:38 +0200 Subject: [PATCH 13/24] Test fixes --- openbb_terminal/portfolio/portfolio_model.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/openbb_terminal/portfolio/portfolio_model.py b/openbb_terminal/portfolio/portfolio_model.py index 433c362c54b0..3a18f2281360 100644 --- a/openbb_terminal/portfolio/portfolio_model.py +++ b/openbb_terminal/portfolio/portfolio_model.py @@ -801,10 +801,10 @@ def __init__(self, trades: pd.DataFrame = pd.DataFrame(), rf: float = 0.0): self.benchmark: pd.DataFrame = pd.DataFrame() self._historical_crypto: pd.DataFrame = pd.DataFrame() self._historical_prices: pd.DataFrame = pd.DataFrame() - self.returns: pd.Series = pd.Series() + self.returns: pd.Series = pd.Series(dtype=object) self.portfolio_value = None self.ItemizedHoldings = None - self.benchmark_returns: pd.Series = pd.Series() + self.benchmark_returns: pd.Series = pd.Series(dtype=object) self.portfolio_sectors_allocation = pd.DataFrame() self.portfolio_assets_allocation = pd.DataFrame() self.benchmark_sectors_allocation = pd.DataFrame() From 6f36908458c1414083f32175ec633b425e60a5c8 Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Sat, 2 Jul 2022 11:09:07 +0200 Subject: [PATCH 14/24] Test fixes --- openbb_terminal/portfolio/portfolio_controller.py | 3 --- openbb_terminal/portfolio/portfolio_model.py | 3 +++ 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/openbb_terminal/portfolio/portfolio_controller.py b/openbb_terminal/portfolio/portfolio_controller.py index 0a1b727e5f92..4c4240f03a52 100644 --- a/openbb_terminal/portfolio/portfolio_controller.py +++ b/openbb_terminal/portfolio/portfolio_controller.py @@ -337,9 +337,6 @@ def call_load(self, other_args: List[str]): # Add in the Risk-free rate self.portfolio.add_rf(ns_parser.risk_free_rate) - # Update all period - portfolio_helper.PERIODS_DAYS["all"] = len(self.portfolio.returns) - console.print(f"\n[bold]Portfolio:[/bold] {self.portfolio_name}") console.print(f"[bold]Risk Free Rate:[/bold] {self.portfolio.rf}") diff --git a/openbb_terminal/portfolio/portfolio_model.py b/openbb_terminal/portfolio/portfolio_model.py index 3a18f2281360..550046b6bec2 100644 --- a/openbb_terminal/portfolio/portfolio_model.py +++ b/openbb_terminal/portfolio/portfolio_model.py @@ -997,6 +997,9 @@ def generate_holdings_from_trades(self, yfinance_use_close: bool = False): returns.replace([np.inf, -np.inf], np.nan, inplace=True) self.returns = returns.dropna() + # Update all period + portfolio_helper.PERIODS_DAYS["all"] = len(self.returns) + self.ItemizedHoldings = pd.DataFrame( { "Stocks": portfolio["StockHoldings"][self._stock_tickers].sum(axis=1), From 8c977c9f0a559d4f3f569b7cfc69fafacb84bfb0 Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Sat, 2 Jul 2022 17:29:05 +0200 Subject: [PATCH 15/24] Adding tests --- .../test_portfolio_helper/test_is_ticker.yaml | 16421 ++++++++++++++++ .../test_common_sense_ratio.csv | 31 + .../test_information_ratio.csv | 31 + .../test_portfolio_model/test_tail_ratio.csv | 31 + .../test_tracking_error.csv | 21 + .../portfolio/test_portfolio_helper.py | 18 + .../portfolio/test_portfolio_model.py | 2434 +++ .../test_portfolio_helper/test_clean_name.txt | 1 + 8 files changed, 18988 insertions(+) create mode 100644 tests/openbb_terminal/portfolio/cassettes/test_portfolio_helper/test_is_ticker.yaml create mode 100644 tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_common_sense_ratio.csv create mode 100644 tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_information_ratio.csv create mode 100644 tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_tail_ratio.csv create mode 100644 tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_tracking_error.csv create mode 100644 tests/openbb_terminal/portfolio/test_portfolio_helper.py create mode 100644 tests/openbb_terminal/portfolio/test_portfolio_model.py create mode 100644 tests/openbb_terminal/portfolio/txt/test_portfolio_helper/test_clean_name.txt diff --git a/tests/openbb_terminal/portfolio/cassettes/test_portfolio_helper/test_is_ticker.yaml b/tests/openbb_terminal/portfolio/cassettes/test_portfolio_helper/test_is_ticker.yaml new file mode 100644 index 000000000000..1847f4a48ac9 --- /dev/null +++ b/tests/openbb_terminal/portfolio/cassettes/test_portfolio_helper/test_is_ticker.yaml @@ -0,0 +1,16421 @@ +interactions: +- request: + body: null + headers: + Accept: + - '*/*' + Accept-Encoding: + - gzip, deflate + Connection: + - keep-alive + User-Agent: + - Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, + like Gecko) Chrome/39.0.2171.95 Safari/537.36 + method: GET + uri: 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X-Content-Type-Options: + - nosniff + X-XSS-Protection: + - 1; mode=block + content-encoding: + - gzip + content-security-policy: + - sandbox allow-downloads allow-forms allow-modals allow-same-origin allow-scripts + allow-popups allow-popups-to-escape-sandbox allow-top-navigation-by-user-activation + allow-presentation; report-uri https://csp.yahoo.com/beacon/csp?src=yahoofinance; + report-to csp-endpoint; + content-type: + - text/html; charset=utf-8 + date: + - Sat, 02 Jul 2022 10:55:26 GMT + referrer-policy: + - no-referrer-when-downgrade + report-to: + - '{"group":"csp-endpoint","max-age":10886400,"endpoints":[{"url":"https://csp.yahoo.com/beacon/csp?src=yahoofinance"}]}' + server: + - ATS + strict-transport-security: + - max-age=15552000 + vary: + - Accept-Encoding + x-envoy-decorator-operation: + - finance-nodejs--mtls-production-ir2.finance-k8s.svc.yahoo.local:4080/* + x-envoy-upstream-service-time: + - '778' + x-frame-options: + - SAMEORIGIN + status: + code: 200 + message: OK 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date: + - Sat, 02 Jul 2022 10:55:28 GMT + referrer-policy: + - no-referrer-when-downgrade + server: + - ATS + strict-transport-security: + - max-age=15552000 + vary: + - Accept-Encoding + x-envoy-decorator-operation: + - finance-nodejs--mtls-production-ir2.finance-k8s.svc.yahoo.local:4080/* + x-envoy-upstream-service-time: + - '374' + status: + code: 200 + message: OK +version: 1 diff --git a/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_common_sense_ratio.csv b/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_common_sense_ratio.csv new file mode 100644 index 000000000000..c046527631cc --- /dev/null +++ b/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_common_sense_ratio.csv @@ -0,0 +1,31 @@ +,Portfolio,Benchmark +mtd,"TotalHoldings NaN +dtype: float64","Adj Close NaN +dtype: float64" +qtd,"TotalHoldings NaN +dtype: float64","Adj Close NaN +dtype: float64" +ytd,"TotalHoldings 0.759 +dtype: float64","Adj Close 0.722 +dtype: float64" +3m,"TotalHoldings 0.64 +dtype: float64","Adj Close 0.588 +dtype: float64" +6m,"TotalHoldings 0.759 +dtype: float64","Adj Close 0.722 +dtype: float64" +1y,"TotalHoldings 0.575 +dtype: float64","Adj Close 0.476 +dtype: float64" +3y,"TotalHoldings -1.168 +dtype: float64","Adj Close -0.794 +dtype: float64" +5y,"TotalHoldings -1.308 +dtype: float64","Adj Close -1.483 +dtype: float64" +10y,"TotalHoldings -1.308 +dtype: float64","Adj Close -1.483 +dtype: float64" +all,"TotalHoldings -1.308 +dtype: float64","Adj Close -1.483 +dtype: float64" diff --git a/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_information_ratio.csv b/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_information_ratio.csv new file mode 100644 index 000000000000..d5ed1b258fba --- /dev/null +++ b/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_information_ratio.csv @@ -0,0 +1,31 @@ +,Information Ratio +mtd,"Adj Close NaN +TotalHoldings NaN +Name: 2022-07-01 00:00:00, dtype: float64" +qtd,"Adj Close NaN +TotalHoldings NaN +Name: 2022-07-01 00:00:00, dtype: float64" +ytd,"Adj Close NaN +TotalHoldings NaN +Name: 2022-07-01 00:00:00, dtype: float64" +3m,"Adj Close NaN +TotalHoldings NaN +Name: 2022-07-01 00:00:00, dtype: float64" +6m,"Adj Close NaN +TotalHoldings NaN +Name: 2022-07-01 00:00:00, dtype: float64" +1y,"Adj Close NaN +TotalHoldings NaN +Name: 2022-07-01 00:00:00, dtype: float64" +3y,"Adj Close NaN +TotalHoldings NaN +Name: 2022-07-01 00:00:00, dtype: float64" +5y,"Adj Close NaN +TotalHoldings NaN +Name: 2022-07-01 00:00:00, dtype: float64" +10y,"Adj Close NaN +TotalHoldings NaN +Name: 2022-07-01 00:00:00, dtype: float64" +all,"Adj Close NaN +TotalHoldings NaN +Name: 2022-07-01 00:00:00, dtype: float64" diff --git a/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_tail_ratio.csv b/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_tail_ratio.csv new file mode 100644 index 000000000000..410c3757722f --- /dev/null +++ b/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_tail_ratio.csv @@ -0,0 +1,31 @@ +,Portfolio,Benchmark +mtd,"TotalHoldings 1.0 +dtype: float64","Adj Close 1.0 +dtype: float64" +qtd,"TotalHoldings 1.0 +dtype: float64","Adj Close 1.0 +dtype: float64" +ytd,"TotalHoldings 0.845 +dtype: float64","Adj Close 0.831 +dtype: float64" +3m,"TotalHoldings 0.762 +dtype: float64","Adj Close 0.71 +dtype: float64" +6m,"TotalHoldings 0.845 +dtype: float64","Adj Close 0.831 +dtype: float64" +1y,"TotalHoldings 0.923 +dtype: float64","Adj Close 0.929 +dtype: float64" +3y,"TotalHoldings 0.912 +dtype: float64","Adj Close 0.797 +dtype: float64" +5y,"TotalHoldings 0.882 +dtype: float64","Adj Close 0.81 +dtype: float64" +10y,"TotalHoldings 0.882 +dtype: float64","Adj Close 0.81 +dtype: float64" +all,"TotalHoldings 0.882 +dtype: float64","Adj Close 0.81 +dtype: float64" diff --git a/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_tracking_error.csv b/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_tracking_error.csv new file mode 100644 index 000000000000..94a7d08d65ff --- /dev/null +++ b/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_tracking_error.csv @@ -0,0 +1,21 @@ +,Tracking Error +mtd,"TotalHoldings NaN +dtype: float64" +qtd,"TotalHoldings NaN +dtype: float64" +ytd,"TotalHoldings 0.02 +dtype: float64" +3m,"TotalHoldings 0.022 +dtype: float64" +6m,"TotalHoldings 0.02 +dtype: float64" +1y,"TotalHoldings 0.015 +dtype: float64" +3y,"TotalHoldings 0.014 +dtype: float64" +5y,"TotalHoldings 0.012 +dtype: float64" +10y,"TotalHoldings 0.012 +dtype: float64" +all,"TotalHoldings 0.012 +dtype: float64" diff --git a/tests/openbb_terminal/portfolio/test_portfolio_helper.py b/tests/openbb_terminal/portfolio/test_portfolio_helper.py new file mode 100644 index 000000000000..908bc9ef8097 --- /dev/null +++ b/tests/openbb_terminal/portfolio/test_portfolio_helper.py @@ -0,0 +1,18 @@ +# IMPORTATION STANDARD + +# IMPORTATION THIRDPARTY +import pytest + +# IMPORTATION INTERNAL +from openbb_terminal.portfolio import portfolio_helper + + +def test_clean_name(recorder): + result = portfolio_helper.clean_name("beta_hello") + recorder.capture(result) + + +@pytest.mark.vcr +def test_is_ticker(): + result = portfolio_helper.is_ticker("aapl") + assert result diff --git a/tests/openbb_terminal/portfolio/test_portfolio_model.py b/tests/openbb_terminal/portfolio/test_portfolio_model.py new file mode 100644 index 000000000000..a7139bf156b9 --- /dev/null +++ b/tests/openbb_terminal/portfolio/test_portfolio_model.py @@ -0,0 +1,2434 @@ +# IMPORTATION STANDARD + +# IMPORTATION THIRDPARTY +import pandas as pd +from io import StringIO +import pytest + +# IMPORTATION INTERNAL +from openbb_terminal.portfolio import portfolio_model + +portfolio_trades = pd.read_csv(StringIO(""",Date,Name,Type,Sector,Industry,Country,Price,Quantity,Fees,Premium,Investment,Side,Currency,Portfolio Investment,Close,Portfolio Value,% Portfolio Return,Abs Portfolio Return +0,2017-10-05,CASH,CASH,CASH,CASH,CASH,8523.0,1,0,0,8523.0,1,USD,0.0,0.0,0.0,0.0,0.0 +1,2018-10-12,QQQ,ETF,American Technology,Large,United States,174.32,30,0,0,5229.599999999999,1,USD,5229.599999999999,282.1300048828125,8463.900146484375,0.6184603309018617,3234.3001464843755 +2,2020-06-05,SPY,ETF,American Market,Large,United States,319.34,10,0,0,3193.3999999999996,1,USD,3193.3999999999996,381.239990234375,3812.39990234375,0.19383725882875624,618.9999023437504 +""")) + +portfolio_returns = pd.read_csv(StringIO("""Date,TotalHoldings +2017-10-06,0.0 +2017-10-09,0.0 +2017-10-10,0.0 +2017-10-11,0.0 +2017-10-12,0.0 +2017-10-13,0.0 +2017-10-16,0.0 +2017-10-17,0.0 +2017-10-18,0.0 +2017-10-19,0.0 +2017-10-20,0.0 +2017-10-23,0.0 +2017-10-24,0.0 +2017-10-25,0.0 +2017-10-26,0.0 +2017-10-27,0.0 +2017-10-30,0.0 +2017-10-31,0.0 +2017-11-01,0.0 +2017-11-02,0.0 +2017-11-03,0.0 +2017-11-06,0.0 +2017-11-07,0.0 +2017-11-08,0.0 +2017-11-09,0.0 +2017-11-10,0.0 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benchmark_returns.set_index("Date") + + +def test_tracking_error(recorder): + result_df, _ = portfolio_model.get_tracking_error(portfolio_returns, benchmark_returns) + + recorder.capture(result_df) + + +def test_information_ratio(recorder): + result_df, _ = portfolio_model.get_information_ratio(portfolio_returns, benchmark_returns) + + recorder.capture(result_df) + + +def test_tail_ratio(recorder): + result_df, _, _ = portfolio_model.get_tail_ratio(portfolio_returns, benchmark_returns) + + recorder.capture(result_df) + + +def test_common_sense_ratio(recorder): + result_df = portfolio_model.get_common_sense_ratio(portfolio_returns, benchmark_returns) + + recorder.capture(result_df) diff --git a/tests/openbb_terminal/portfolio/txt/test_portfolio_helper/test_clean_name.txt b/tests/openbb_terminal/portfolio/txt/test_portfolio_helper/test_clean_name.txt new file mode 100644 index 000000000000..d9605cba788b --- /dev/null +++ b/tests/openbb_terminal/portfolio/txt/test_portfolio_helper/test_clean_name.txt @@ -0,0 +1 @@ +HELLO \ No newline at end of file From 2f7d1498f0259c62e7cd26c9f9edcaa7f272c25c Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Sat, 2 Jul 2022 17:34:06 +0200 Subject: [PATCH 16/24] Linting --- .../portfolio/test_portfolio_model.py | 40 ++++++++++++++----- 1 file changed, 30 insertions(+), 10 deletions(-) diff --git a/tests/openbb_terminal/portfolio/test_portfolio_model.py b/tests/openbb_terminal/portfolio/test_portfolio_model.py index a7139bf156b9..bc3d986cae5b 100644 --- a/tests/openbb_terminal/portfolio/test_portfolio_model.py +++ b/tests/openbb_terminal/portfolio/test_portfolio_model.py @@ -8,13 +8,19 @@ # IMPORTATION INTERNAL from openbb_terminal.portfolio import portfolio_model -portfolio_trades = pd.read_csv(StringIO(""",Date,Name,Type,Sector,Industry,Country,Price,Quantity,Fees,Premium,Investment,Side,Currency,Portfolio Investment,Close,Portfolio Value,% Portfolio Return,Abs Portfolio Return +portfolio_trades = pd.read_csv( + StringIO( + """,Date,Name,Type,Sector,Industry,Country,Price,Quantity,Fees,Premium,Investment,Side,Currency,Portfolio Investment,Close,Portfolio Value,% Portfolio Return,Abs Portfolio Return 0,2017-10-05,CASH,CASH,CASH,CASH,CASH,8523.0,1,0,0,8523.0,1,USD,0.0,0.0,0.0,0.0,0.0 1,2018-10-12,QQQ,ETF,American Technology,Large,United States,174.32,30,0,0,5229.599999999999,1,USD,5229.599999999999,282.1300048828125,8463.900146484375,0.6184603309018617,3234.3001464843755 2,2020-06-05,SPY,ETF,American Market,Large,United States,319.34,10,0,0,3193.3999999999996,1,USD,3193.3999999999996,381.239990234375,3812.39990234375,0.19383725882875624,618.9999023437504 -""")) +""" + ) +) -portfolio_returns = pd.read_csv(StringIO("""Date,TotalHoldings +portfolio_returns = pd.read_csv( + StringIO( + """Date,TotalHoldings 2017-10-06,0.0 2017-10-09,0.0 2017-10-10,0.0 @@ -1206,12 +1212,16 @@ 2022-06-28,-0.027172133902980122 2022-06-29,0.00037859625879343994 2022-06-30,-0.01099261022575082 -2022-07-01,0.007768167295043371""")) +2022-07-01,0.007768167295043371""" + ) +) portfolio_returns["Date"] = pd.to_datetime(portfolio_returns["Date"]) portfolio_returns = portfolio_returns.set_index("Date") -benchmark_returns = pd.read_csv(StringIO("""Date,Adj Close +benchmark_returns = pd.read_csv( + StringIO( + """Date,Adj Close 2017-10-05,0.005925101432529667 2017-10-06,-0.0011386985711221431 2017-10-09,-0.0016512406993203221 @@ -2404,31 +2414,41 @@ 2022-06-28,-0.02043285343481205 2022-06-29,-0.000814390026440015 2022-06-30,-0.008124300277758567 -2022-07-01,0.010576514869118592""")) +2022-07-01,0.010576514869118592""" + ) +) benchmark_returns["Date"] = pd.to_datetime(benchmark_returns["Date"]) benchmark_returns = benchmark_returns.set_index("Date") def test_tracking_error(recorder): - result_df, _ = portfolio_model.get_tracking_error(portfolio_returns, benchmark_returns) + result_df, _ = portfolio_model.get_tracking_error( + portfolio_returns, benchmark_returns + ) recorder.capture(result_df) def test_information_ratio(recorder): - result_df, _ = portfolio_model.get_information_ratio(portfolio_returns, benchmark_returns) + result_df, _ = portfolio_model.get_information_ratio( + portfolio_returns, benchmark_returns + ) recorder.capture(result_df) def test_tail_ratio(recorder): - result_df, _, _ = portfolio_model.get_tail_ratio(portfolio_returns, benchmark_returns) + result_df, _, _ = portfolio_model.get_tail_ratio( + portfolio_returns, benchmark_returns + ) recorder.capture(result_df) def test_common_sense_ratio(recorder): - result_df = portfolio_model.get_common_sense_ratio(portfolio_returns, benchmark_returns) + result_df = portfolio_model.get_common_sense_ratio( + portfolio_returns, benchmark_returns + ) recorder.capture(result_df) From 52a8ddb6bbd7dcd85ec1cfa1ad7ec84841792415 Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Sat, 2 Jul 2022 17:48:24 +0200 Subject: [PATCH 17/24] Restructuring added tests --- .../portfolio/benchmark_returns.csv | 1194 ++++++++ .../portfolio/example_portfolio.csv | 4 + .../portfolio/portfolio_returns.csv | 1193 ++++++++ .../portfolio/test_portfolio_model.py | 2408 +---------------- 4 files changed, 2394 insertions(+), 2405 deletions(-) create mode 100644 tests/openbb_terminal/portfolio/benchmark_returns.csv create mode 100644 tests/openbb_terminal/portfolio/example_portfolio.csv create mode 100644 tests/openbb_terminal/portfolio/portfolio_returns.csv diff --git a/tests/openbb_terminal/portfolio/benchmark_returns.csv b/tests/openbb_terminal/portfolio/benchmark_returns.csv new file mode 100644 index 000000000000..37256049864c --- /dev/null +++ b/tests/openbb_terminal/portfolio/benchmark_returns.csv @@ -0,0 +1,1194 @@ +Date,Adj Close +2017-10-05,0.005925101432529667 +2017-10-06,-0.0011386985711221431 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Return,Abs Portfolio Return -0,2017-10-05,CASH,CASH,CASH,CASH,CASH,8523.0,1,0,0,8523.0,1,USD,0.0,0.0,0.0,0.0,0.0 -1,2018-10-12,QQQ,ETF,American Technology,Large,United States,174.32,30,0,0,5229.599999999999,1,USD,5229.599999999999,282.1300048828125,8463.900146484375,0.6184603309018617,3234.3001464843755 -2,2020-06-05,SPY,ETF,American Market,Large,United States,319.34,10,0,0,3193.3999999999996,1,USD,3193.3999999999996,381.239990234375,3812.39990234375,0.19383725882875624,618.9999023437504 -""" - ) -) +portfolio_trades = pd.read_csv("example_portfolio.csv") -portfolio_returns = pd.read_csv( - StringIO( - """Date,TotalHoldings -2017-10-06,0.0 -2017-10-09,0.0 -2017-10-10,0.0 -2017-10-11,0.0 -2017-10-12,0.0 -2017-10-13,0.0 -2017-10-16,0.0 -2017-10-17,0.0 -2017-10-18,0.0 -2017-10-19,0.0 -2017-10-20,0.0 -2017-10-23,0.0 -2017-10-24,0.0 -2017-10-25,0.0 -2017-10-26,0.0 -2017-10-27,0.0 -2017-10-30,0.0 -2017-10-31,0.0 -2017-11-01,0.0 -2017-11-02,0.0 -2017-11-03,0.0 -2017-11-06,0.0 -2017-11-07,0.0 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-2022-05-27,0.02989771703051458 -2022-05-31,-0.003539916781935659 -2022-06-01,-0.007552661581325171 -2022-06-02,0.024630106784876205 -2022-06-03,-0.022907942011826443 -2022-06-06,0.0032185522193024507 -2022-06-07,0.008857065282661392 -2022-06-08,-0.008268798124287935 -2022-06-09,-0.025668033211193264 -2022-06-10,-0.03308035155431721 -2022-06-13,-0.043507343829187084 -2022-06-14,0.0003078707678412229 -2022-06-15,0.021464188504486392 -2022-06-16,-0.037801789234995664 -2022-06-17,0.008982209485447923 -2022-06-21,0.025001897879974422 -2022-06-22,-0.0015549105361214455 -2022-06-23,0.013217514849510836 -2022-06-24,0.033236434786762414 -2022-06-27,-0.006207530141609352 -2022-06-28,-0.027172133902980122 -2022-06-29,0.00037859625879343994 -2022-06-30,-0.01099261022575082 -2022-07-01,0.007768167295043371""" - ) -) +portfolio_returns = pd.read_csv("portfolio_returns.csv") portfolio_returns["Date"] = pd.to_datetime(portfolio_returns["Date"]) portfolio_returns = portfolio_returns.set_index("Date") -benchmark_returns = pd.read_csv( - StringIO( - """Date,Adj Close -2017-10-05,0.005925101432529667 -2017-10-06,-0.0011386985711221431 -2017-10-09,-0.0016512406993203221 -2017-10-10,0.002638308045010307 -2017-10-11,0.0015710538977629085 -2017-10-12,-0.0014900172222770403 -2017-10-13,0.0012172823660669962 -2017-10-16,0.001333563355853551 -2017-10-17,0.0007053004565025223 -2017-10-18,0.0009783497735593727 -2017-10-19,0.00027366760110392185 -2017-10-20,0.005160582940256786 -2017-10-23,-0.003889339637327738 -2017-10-24,0.001757120605978102 -2017-10-25,-0.0049502291965218825 -2017-10-26,0.0012927373123921004 -2017-10-27,0.008176247634272382 -2017-10-30,-0.003725036647947655 -2017-10-31,0.0015578265968012595 -2017-11-01,0.0013220253977763718 -2017-11-02,0.00038857866836883304 -2017-11-03,0.003338537013492182 -2017-11-06,0.0015478362585690242 -2017-11-07,-0.0006956002150839691 -2017-11-08,0.0017008710241948055 -2017-11-09,-0.0036275788020553312 -2017-11-10,-0.0003098131884202715 -2017-11-13,0.0009297276071351668 -2017-11-14,-0.002322416456726706 -2017-11-15,-0.005005310190766554 -2017-11-16,0.00850094581594707 -2017-11-17,-0.0029388086081684195 -2017-11-20,0.0017065351633391845 -2017-11-21,0.0065426156999439655 -2017-11-22,-0.0008844619225002459 -2017-11-24,0.0023098860739683147 -2017-11-27,-0.0004995456132084186 -2017-11-28,0.01014500426805065 -2017-11-29,-0.0006086107491077852 -2017-11-30,0.008754745591897706 -2017-12-01,-0.0020754125939358437 -2017-12-04,-0.0012098407814215006 -2017-12-05,-0.003596490628629767 -2017-12-06,0.00018970397559758823 -2017-12-07,0.0031532697315421743 -2017-12-08,0.005452918519209815 -2017-12-11,0.003013295410539074 -2017-12-12,0.0017647508735143536 -2017-12-13,-0.00011253900534891059 -2017-12-14,-0.004086252697934389 -2017-12-15,0.008327715385572088 -2017-12-18,0.006340964238781721 -2017-12-19,-0.003840279652267742 -2017-12-20,-0.0005241740435426578 -2017-12-21,0.0020597886606485982 -2017-12-22,-0.0002616238832495732 -2017-12-26,-0.0011961846992444292 -2017-12-27,0.0004866437802675261 -2017-12-28,0.0020571838941076948 -2017-12-29,-0.0037705882674945457 -2018-01-02,0.007157609722737268 -2018-01-03,0.006324978085097355 -2018-01-04,0.004214779475008923 -2018-01-05,0.006664292454853227 -2018-01-08,0.0018282848764425985 -2018-01-09,0.002264028241618643 -2018-01-10,-0.0015303075612136396 -2018-01-11,0.007296029280764449 -2018-01-12,0.006519103201004572 -2018-01-16,-0.003418331795749907 -2018-01-17,0.009531372688985629 -2018-01-18,-0.001680275151243027 -2018-01-19,0.004549619967851193 -2018-01-22,0.008130510265931035 -2018-01-23,0.002122744794927467 -2018-01-24,-0.0003884986713112992 -2018-01-25,0.00042402376208672266 -2018-01-26,0.01157754892060514 -2018-01-29,-0.0066297268955874955 -2018-01-30,-0.010257216344550568 -2018-01-31,0.0004967976549465902 -2018-02-01,-0.0011350070420699243 -2018-02-02,-0.021769737129274436 -2018-02-05,-0.04182259129201893 -2018-02-06,0.019702191133402325 -2018-02-07,-0.005424993316478277 -2018-02-08,-0.03750895432778867 -2018-02-09,0.01502147061789727 -2018-02-12,0.014684685916397378 -2018-02-13,0.0024871911765564914 -2018-02-14,0.013496587482045408 -2018-02-15,0.012759740466099068 -2018-02-16,0.0002932718017714109 -2018-02-20,-0.006261507995828808 -2018-02-21,-0.004974040723319306 -2018-02-22,0.0012961548889534047 -2018-02-23,0.01593934157943755 -2018-02-26,0.011612108461084958 -2018-02-27,-0.012486685733995917 -2018-02-28,-0.010129900225916089 -2018-03-01,-0.014540602502441158 -2018-03-02,0.005154800335496423 -2018-03-05,0.01155798537244146 -2018-03-06,0.002535126286599798 -2018-03-07,-0.0003666100369278391 -2018-03-08,0.004839372316082002 -2018-03-09,0.017402164106880225 -2018-03-12,-0.00125521959489594 -2018-03-13,-0.006462395819998967 -2018-03-14,-0.005131811072284886 -2018-03-15,-0.0010895040276039936 -2018-03-16,0.0010841619669439417 -2018-03-19,-0.013530046598519863 -2018-03-20,0.0017005747227898382 -2018-03-21,-0.0019192937289788103 -2018-03-22,-0.0249971601238671 -2018-03-23,-0.021314630410460222 -2018-03-26,0.02735906307676239 -2018-03-27,-0.01701183610506929 -2018-03-28,-0.002954743552591288 -2018-03-29,0.012777665885229217 -2018-04-02,-0.021584675940823028 -2018-04-03,0.012817093162710735 -2018-04-04,0.010698935310696545 -2018-04-05,0.007892064619119843 -2018-04-06,-0.02228575195100324 -2018-04-09,0.00492824198129993 -2018-04-10,0.0159004676597041 -2018-04-11,-0.0052422858331842015 -2018-04-12,0.008227020830350762 -2018-04-13,-0.0029329789322265487 -2018-04-16,0.0082216450135002 -2018-04-17,0.010698447781280596 -2018-04-18,0.0007403598646968934 -2018-04-19,-0.005547741369930637 -2018-04-20,-0.00847926047915426 -2018-04-23,-0.0001498756124742595 -2018-04-24,-0.013467495909813887 -2018-04-25,0.0024719199281149073 -2018-04-26,0.010165504175668083 -2018-04-27,0.0009388407141128763 -2018-04-30,-0.007690583480020385 -2018-05-01,0.001776741088702627 -2018-05-02,-0.006717520434772584 -2018-05-03,-0.0022035656201865317 -2018-05-04,0.012946161947184232 -2018-05-07,0.003383660126848431 -2018-05-08,0.0 -2018-05-09,0.009665799811874098 -2018-05-10,0.009350529056310952 -2018-05-11,0.0030510692134713135 -2018-05-14,0.00047669281280038334 -2018-05-15,-0.006886870839566628 -2018-05-16,0.004204795482537049 -2018-05-17,-0.0008447314412248774 -2018-05-18,-0.002499777688947158 -2018-05-21,0.0075184895912399075 -2018-05-22,-0.0027801602424959437 -2018-05-23,0.0027510712154350525 -2018-05-24,-0.0020486080678875362 -2018-05-25,-0.0023826375507143283 -2018-05-29,-0.011501045711317381 -2018-05-30,0.013344848349060578 -2018-05-31,-0.006125891937113659 -2018-06-01,0.009817347228507689 -2018-06-04,0.004751641944409579 -2018-06-05,0.0007276152212638554 -2018-06-06,0.008360626156670437 -2018-06-07,-0.00010825626138244449 -2018-06-08,0.002956603352970655 -2018-06-11,0.0013295991299915322 -2018-06-12,0.0012926054040118817 -2018-06-13,-0.003191041221489055 -2018-06-14,0.002517777249724018 -2018-06-15,-0.0012756853246733701 -2018-06-18,-0.0020569790385500664 -2018-06-19,-0.003832872442718682 -2018-06-20,0.0017063636167413687 -2018-06-21,-0.00626874033458702 -2018-06-22,0.001822978657293639 -2018-06-25,-0.01361279445222674 -2018-06-26,0.002214006079640063 -2018-06-27,-0.008284346981743185 -2018-06-28,0.005717550529250159 -2018-06-29,0.0014398361379028835 -2018-07-02,0.002137890279696242 -2018-07-03,-0.0035311917632486756 -2018-07-05,0.008158066272951014 -2018-07-06,0.008458071327168692 -2018-07-09,0.009004308667634797 -2018-07-10,0.0035984105197837124 -2018-07-11,-0.007314643297796075 -2018-07-12,0.009066169120762302 -2018-07-13,0.000787447343186809 -2018-07-16,-0.000893989654962013 -2018-07-17,0.004045150731692315 -2018-07-18,0.0021037781567738723 -2018-07-19,-0.0037715038085295305 -2018-07-20,-0.0011428643443127662 -2018-07-23,0.0018591334340043453 -2018-07-24,0.005032174197767247 -2018-07-25,0.008522479075518508 -2018-07-26,-0.0023590652367935228 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-2018-09-07,-0.0019433206643505452 -2018-09-10,0.0017385226885560101 -2018-09-11,0.003297607830880178 -2018-09-12,0.0002421247019079864 -2018-09-13,0.005914232887243909 -2018-09-14,0.00017233714673281497 -2018-09-17,-0.005294691234369431 -2018-09-18,0.0054264250435376304 -2018-09-19,0.0010654107862790863 -2018-09-20,0.008104032112754567 -2018-09-21,-0.0009138232714094308 -2018-09-24,-0.003321779881398368 -2018-09-25,-0.0009277664366716953 -2018-09-26,-0.0029926186324770176 -2018-09-27,0.002794694893305749 -2018-09-28,0.00010305298669033292 -2018-10-01,0.0034742395758546873 -2018-10-02,-0.0005827770917203878 -2018-10-03,0.0005488684218482032 -2018-10-04,-0.007815857988851871 -2018-10-05,-0.00559709836855149 -2018-10-08,0.0 -2018-10-09,-0.001459049593786177 -2018-10-10,-0.03166364870982341 -2018-10-11,-0.022026198484844994 -2018-10-12,0.013888545308248013 -2018-10-15,-0.005617296137718442 -2018-10-16,0.021866055784051763 -2018-10-17,0.0001785219841297092 -2018-10-18,-0.01444146277930114 -2018-10-19,-0.000542492904345826 -2018-10-22,-0.004488651328822368 -2018-10-23,-0.005090670998266877 -2018-10-24,-0.030298743514052262 -2018-10-25,0.017940623437721737 -2018-10-26,-0.017587397607214506 -2018-10-29,-0.005540201181359561 -2018-10-30,0.014818352664848655 -2018-10-31,0.01068092222977235 -2018-11-01,0.010641960359537572 -2018-11-02,-0.005923147671804241 -2018-11-05,0.005517127607643779 -2018-11-06,0.006327578570061165 -2018-11-07,0.021408876846761737 -2018-11-08,-0.0018146799482380294 -2018-11-09,-0.009768593235838008 -2018-11-12,-0.018685025643415676 -2018-11-13,-0.0018711092145445862 -2018-11-14,-0.006836732351582442 -2018-11-15,0.010436740891114793 -2018-11-16,0.002600462645988566 -2018-11-19,-0.016914478727248383 -2018-11-20,-0.018506179735794492 -2018-11-21,0.003407771398537207 -2018-11-23,-0.006678747437234067 -2018-11-26,0.016144155871915755 -2018-11-27,0.0033647123482218877 -2018-11-28,0.02302513423653263 -2018-11-29,-0.002184947094547529 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pd.read_csv("benchmark_returns.csv") benchmark_returns["Date"] = pd.to_datetime(benchmark_returns["Date"]) benchmark_returns = benchmark_returns.set_index("Date") From e43eadb4ce558c26f0462e5f56a19d9c5abc9c79 Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Sat, 2 Jul 2022 19:22:50 +0200 Subject: [PATCH 18/24] Linting --- tests/openbb_terminal/portfolio/test_portfolio_model.py | 1 - 1 file changed, 1 deletion(-) diff --git a/tests/openbb_terminal/portfolio/test_portfolio_model.py b/tests/openbb_terminal/portfolio/test_portfolio_model.py index 242c3a8714a8..20b7dd65d112 100644 --- a/tests/openbb_terminal/portfolio/test_portfolio_model.py +++ b/tests/openbb_terminal/portfolio/test_portfolio_model.py @@ -2,7 +2,6 @@ # IMPORTATION THIRDPARTY import pandas as pd -import pytest # IMPORTATION INTERNAL from openbb_terminal.portfolio import portfolio_model From 02108cd26af1c2b5de1b603e96817694ef547acd Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Mon, 4 Jul 2022 10:08:19 +0200 Subject: [PATCH 19/24] Updating hugo website and fixing help --- openbb_terminal/portfolio/portfolio_controller.py | 2 +- website/content/terminal/portfolio/metric/_index.md | 6 +++--- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/openbb_terminal/portfolio/portfolio_controller.py b/openbb_terminal/portfolio/portfolio_controller.py index 83a30e5f18b3..cb61f57fbf8a 100644 --- a/openbb_terminal/portfolio/portfolio_controller.py +++ b/openbb_terminal/portfolio/portfolio_controller.py @@ -1141,7 +1141,7 @@ def call_metric(self, other_args: List[str]): dest="metric", default="-h" not in other_args, choices=self.VALID_METRICS, - help="Period to apply rolling window", + help="Set metric of choice", ) parser.add_argument( "-r", diff --git a/website/content/terminal/portfolio/metric/_index.md b/website/content/terminal/portfolio/metric/_index.md index 64ac6e914376..92a90f5db516 100644 --- a/website/content/terminal/portfolio/metric/_index.md +++ b/website/content/terminal/portfolio/metric/_index.md @@ -1,13 +1,13 @@ ``` -usage: metric [-m {volatility,sharpe,sortino,maxdrawdown,rsquare,skew,kurtosis}] [-r RISK_FREE_RATE] [-h] [--export EXPORT] +usage: metric [-m {volatility,sharpe,sortino,maxdrawdown,rsquare,skew,kurtosis,gaintopain,trackerr,information,tail,commonsense,jensens,calmar,kelly,payoff,profitfactor}] [-r RISK_FREE_RATE] [-h] [--export EXPORT] ``` Display metric of choice for different periods ``` optional arguments: - -m {volatility,sharpe,sortino,maxdrawdown,rsquare,skew,kurtosis}, --metric {volatility,sharpe,sortino,maxdrawdown,rsquare,skew,kurtosis} - Period to apply rolling window (default: False) + -m {volatility,sharpe,sortino,maxdrawdown,rsquare,skew,kurtosis,gaintopain,trackerr,information,tail,commonsense,jensens,calmar,kelly,payoff,profitfactor}, --metric {volatility,sharpe,sortino,maxdrawdown,rsquare,skew,kurtosis,gaintopain,trackerr,information,tail,commonsense,jensens,calmar,kelly,payoff,profitfactor} + Set metric of choice (default: False) -r RISK_FREE_RATE, --rfr RISK_FREE_RATE Set risk free rate for calculations. (default: 0.0) -h, --help show this help message (default: False) From 282f9a057d59cfab8e70e75f456280f8b2588b66 Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Mon, 4 Jul 2022 18:04:41 +0200 Subject: [PATCH 20/24] Fixing commands --- openbb_terminal/portfolio/portfolio_model.py | 59 ++++++++++++++------ 1 file changed, 42 insertions(+), 17 deletions(-) diff --git a/openbb_terminal/portfolio/portfolio_model.py b/openbb_terminal/portfolio/portfolio_model.py index 550046b6bec2..6bb64a0f4fe8 100644 --- a/openbb_terminal/portfolio/portfolio_model.py +++ b/openbb_terminal/portfolio/portfolio_model.py @@ -298,7 +298,7 @@ def get_tracking_error( vals = list() for periods in portfolio_helper.PERIODS: - period_return = portfolio_helper.filter_df_by_period(returns, periods) + period_return = portfolio_helper.filter_df_by_period(diff_returns, periods) if not period_return.empty: vals.append([round(period_return.std(), 3)]) else: @@ -332,26 +332,46 @@ def get_information_ratio( pd.Series Series of rolling information ratio """ - diff_returns = returns - benchmark_returns - _, tracking_err = get_tracking_error(returns, benchmark_returns, period) + tracking_err_df, tracking_err_rol = get_tracking_error( + returns, benchmark_returns, period + ) ir_rolling = ( - (1.0 + diff_returns).rolling(window=period).agg(lambda x: x.prod()) - 1 - ) / tracking_err + (1.0 + returns).rolling(window=period).agg(lambda x: x.prod()) + - 1 + - ((1.0 + benchmark_returns).rolling(window=period).agg(lambda x: x.prod()) - 1) + ) / tracking_err_rol vals = list() for periods in portfolio_helper.PERIODS: period_return = portfolio_helper.filter_df_by_period(returns, periods) - period_track_err = portfolio_helper.filter_df_by_period(tracking_err, periods) + period_bench_return = portfolio_helper.filter_df_by_period( + benchmark_returns, periods + ) if not period_return.empty: vals.append( [ round( ( - (1 + period_return.shift(periods=1, fill_value=0)).cumprod() - - 1 - ).iloc[-1] - / period_track_err.iloc[-1], + ( + ( + 1 + period_return.shift(periods=1, fill_value=0) + ).cumprod() + - 1 + ).iloc[-1] + - ( + ( + ( + 1 + + period_bench_return.shift( + periods=1, fill_value=0 + ) + ).cumprod() + - 1 + ).iloc[-1] + ) + ) + / tracking_err_df.loc[periods, "Tracking Error"], 3, ) ] @@ -614,10 +634,12 @@ def get_calmar_ratio( period_cum_bench_returns = ( (1 + period_bench_return.shift(periods=1, fill_value=0)).cumprod() - 1 ).iloc[-1] - annual_return = period_cum_returns ** (1 / (periods_d[periods] / 252)) - 1 - annual_bench_return = ( - period_cum_bench_returns ** (1 / (periods_d[periods] / 252)) - 1 - ) + annual_return = (1 + period_cum_returns) ** ( + 1 / (len(period_return) / 252) + ) - 1 + annual_bench_return = (1 + period_cum_bench_returns) ** ( + 1 / (len(period_bench_return) / 252) + ) - 1 drawdown = portfolio_helper.get_maximum_drawdown(period_return) bench_drawdown = portfolio_helper.get_maximum_drawdown(period_bench_return) if (drawdown != 0) and (bench_drawdown != 0): @@ -669,7 +691,10 @@ def get_kelly_criterion(returns: pd.Series, portfolio_trades: pd.DataFrame): r = len( period_portfolio_tr[period_portfolio_tr["% Portfolio Return"] > 0] ) / len(period_portfolio_tr) - vals.append([round(w - (1 - w) / r, 3)]) + if r != 0: + vals.append([round(w - (1 - w) / r, 3)]) + else: + vals.append(["-"]) else: vals.append(["-"]) @@ -711,7 +736,7 @@ def get_payoff_ratio(portfolio_trades: pd.DataFrame): ] avg_w = portfolio_wins["Abs Portfolio Return"].mean() avg_l = portfolio_loses["Abs Portfolio Return"].mean() - vals.append([round(avg_w / avg_l, 3)]) + vals.append([round(avg_w / abs(avg_l), 3)] if avg_w is not np.nan else [0]) else: vals.append(["-"]) @@ -753,7 +778,7 @@ def get_profit_factor(portfolio_trades: pd.DataFrame): ] gross_profit = portfolio_wins["Abs Portfolio Return"].sum() gross_loss = portfolio_loses["Abs Portfolio Return"].sum() - vals.append([round(gross_profit / gross_loss, 3)]) + vals.append([round(gross_profit / abs(gross_loss), 3)]) else: vals.append(["-"]) From ea09aed27fc250369e99d8537f9562e2cc9c15c8 Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Tue, 5 Jul 2022 11:43:30 +0200 Subject: [PATCH 21/24] Fix kelly criterion command --- openbb_terminal/portfolio/portfolio_model.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/openbb_terminal/portfolio/portfolio_model.py b/openbb_terminal/portfolio/portfolio_model.py index 6bb64a0f4fe8..b3ca4a76ea9f 100644 --- a/openbb_terminal/portfolio/portfolio_model.py +++ b/openbb_terminal/portfolio/portfolio_model.py @@ -690,7 +690,9 @@ def get_kelly_criterion(returns: pd.Series, portfolio_trades: pd.DataFrame): w = len(period_return[period_return > 0]) / len(period_return) r = len( period_portfolio_tr[period_portfolio_tr["% Portfolio Return"] > 0] - ) / len(period_portfolio_tr) + ) / len( + period_portfolio_tr[period_portfolio_tr["Type"].str.upper() != "CASH"] + ) if r != 0: vals.append([round(w - (1 - w) / r, 3)]) else: From c49ef21d15ffbdf176323dd06893cea214260994 Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Wed, 6 Jul 2022 23:08:26 +0200 Subject: [PATCH 22/24] Fixing tests --- .../benchmark_returns.csv | 0 .../example_portfolio.csv | 0 .../portfolio_returns.csv | 0 .../test_common_sense_ratio.csv | 16 +++++----- .../test_information_ratio.csv | 20 ++++++------- .../test_portfolio_model/test_tail_ratio.csv | 14 ++++----- .../test_tracking_error.csv | 30 ++++++++++++------- .../portfolio/test_portfolio_model.py | 14 +++++++-- 8 files changed, 56 insertions(+), 38 deletions(-) rename tests/openbb_terminal/portfolio/{ => csv/test_portfolio_model}/benchmark_returns.csv (100%) rename tests/openbb_terminal/portfolio/{ => csv/test_portfolio_model}/example_portfolio.csv (100%) rename tests/openbb_terminal/portfolio/{ => csv/test_portfolio_model}/portfolio_returns.csv (100%) diff --git a/tests/openbb_terminal/portfolio/benchmark_returns.csv b/tests/openbb_terminal/portfolio/csv/test_portfolio_model/benchmark_returns.csv similarity index 100% rename from tests/openbb_terminal/portfolio/benchmark_returns.csv rename to tests/openbb_terminal/portfolio/csv/test_portfolio_model/benchmark_returns.csv diff --git a/tests/openbb_terminal/portfolio/example_portfolio.csv b/tests/openbb_terminal/portfolio/csv/test_portfolio_model/example_portfolio.csv similarity index 100% rename from tests/openbb_terminal/portfolio/example_portfolio.csv rename to tests/openbb_terminal/portfolio/csv/test_portfolio_model/example_portfolio.csv diff --git a/tests/openbb_terminal/portfolio/portfolio_returns.csv b/tests/openbb_terminal/portfolio/csv/test_portfolio_model/portfolio_returns.csv similarity index 100% rename from tests/openbb_terminal/portfolio/portfolio_returns.csv rename to tests/openbb_terminal/portfolio/csv/test_portfolio_model/portfolio_returns.csv diff --git a/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_common_sense_ratio.csv b/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_common_sense_ratio.csv index c046527631cc..c49df71b3c83 100644 --- a/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_common_sense_ratio.csv +++ b/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_common_sense_ratio.csv @@ -8,17 +8,17 @@ dtype: float64" ytd,"TotalHoldings 0.759 dtype: float64","Adj Close 0.722 dtype: float64" -3m,"TotalHoldings 0.64 -dtype: float64","Adj Close 0.588 +3m,"TotalHoldings 0.658 +dtype: float64","Adj Close 0.584 dtype: float64" -6m,"TotalHoldings 0.759 -dtype: float64","Adj Close 0.722 +6m,"TotalHoldings 0.751 +dtype: float64","Adj Close 0.714 dtype: float64" -1y,"TotalHoldings 0.575 -dtype: float64","Adj Close 0.476 +1y,"TotalHoldings 0.582 +dtype: float64","Adj Close 0.469 dtype: float64" -3y,"TotalHoldings -1.168 -dtype: float64","Adj Close -0.794 +3y,"TotalHoldings -1.153 +dtype: float64","Adj Close -0.774 dtype: float64" 5y,"TotalHoldings -1.308 dtype: float64","Adj Close -1.483 diff --git a/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_information_ratio.csv b/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_information_ratio.csv index d5ed1b258fba..5059a8bab22e 100644 --- a/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_information_ratio.csv +++ b/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_information_ratio.csv @@ -1,31 +1,31 @@ ,Information Ratio mtd,"Adj Close NaN TotalHoldings NaN -Name: 2022-07-01 00:00:00, dtype: float64" +dtype: float64" qtd,"Adj Close NaN TotalHoldings NaN -Name: 2022-07-01 00:00:00, dtype: float64" +dtype: float64" ytd,"Adj Close NaN TotalHoldings NaN -Name: 2022-07-01 00:00:00, dtype: float64" +dtype: float64" 3m,"Adj Close NaN TotalHoldings NaN -Name: 2022-07-01 00:00:00, dtype: float64" +dtype: float64" 6m,"Adj Close NaN TotalHoldings NaN -Name: 2022-07-01 00:00:00, dtype: float64" +dtype: float64" 1y,"Adj Close NaN TotalHoldings NaN -Name: 2022-07-01 00:00:00, dtype: float64" +dtype: float64" 3y,"Adj Close NaN TotalHoldings NaN -Name: 2022-07-01 00:00:00, dtype: float64" +dtype: float64" 5y,"Adj Close NaN TotalHoldings NaN -Name: 2022-07-01 00:00:00, dtype: float64" +dtype: float64" 10y,"Adj Close NaN TotalHoldings NaN -Name: 2022-07-01 00:00:00, dtype: float64" +dtype: float64" all,"Adj Close NaN TotalHoldings NaN -Name: 2022-07-01 00:00:00, dtype: float64" +dtype: float64" diff --git a/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_tail_ratio.csv b/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_tail_ratio.csv index 410c3757722f..bc7d1d0698be 100644 --- a/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_tail_ratio.csv +++ b/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_tail_ratio.csv @@ -8,17 +8,17 @@ dtype: float64" ytd,"TotalHoldings 0.845 dtype: float64","Adj Close 0.831 dtype: float64" -3m,"TotalHoldings 0.762 -dtype: float64","Adj Close 0.71 +3m,"TotalHoldings 0.76 +dtype: float64","Adj Close 0.706 dtype: float64" -6m,"TotalHoldings 0.845 -dtype: float64","Adj Close 0.831 +6m,"TotalHoldings 0.846 +dtype: float64","Adj Close 0.833 dtype: float64" 1y,"TotalHoldings 0.923 -dtype: float64","Adj Close 0.929 +dtype: float64","Adj Close 0.928 dtype: float64" -3y,"TotalHoldings 0.912 -dtype: float64","Adj Close 0.797 +3y,"TotalHoldings 0.911 +dtype: float64","Adj Close 0.798 dtype: float64" 5y,"TotalHoldings 0.882 dtype: float64","Adj Close 0.81 diff --git a/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_tracking_error.csv b/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_tracking_error.csv index 94a7d08d65ff..0f9f53b207ea 100644 --- a/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_tracking_error.csv +++ b/tests/openbb_terminal/portfolio/csv/test_portfolio_model/test_tracking_error.csv @@ -1,21 +1,31 @@ ,Tracking Error -mtd,"TotalHoldings NaN +mtd,"Adj Close NaN +TotalHoldings NaN dtype: float64" -qtd,"TotalHoldings NaN +qtd,"Adj Close NaN +TotalHoldings NaN dtype: float64" -ytd,"TotalHoldings 0.02 +ytd,"Adj Close NaN +TotalHoldings NaN dtype: float64" -3m,"TotalHoldings 0.022 +3m,"Adj Close NaN +TotalHoldings NaN dtype: float64" -6m,"TotalHoldings 0.02 +6m,"Adj Close NaN +TotalHoldings NaN dtype: float64" -1y,"TotalHoldings 0.015 +1y,"Adj Close NaN +TotalHoldings NaN dtype: float64" -3y,"TotalHoldings 0.014 +3y,"Adj Close NaN +TotalHoldings NaN dtype: float64" -5y,"TotalHoldings 0.012 +5y,"Adj Close NaN +TotalHoldings NaN dtype: float64" -10y,"TotalHoldings 0.012 +10y,"Adj Close NaN +TotalHoldings NaN dtype: float64" -all,"TotalHoldings 0.012 +all,"Adj Close NaN +TotalHoldings NaN dtype: float64" diff --git a/tests/openbb_terminal/portfolio/test_portfolio_model.py b/tests/openbb_terminal/portfolio/test_portfolio_model.py index 20b7dd65d112..4479e86e9ec9 100644 --- a/tests/openbb_terminal/portfolio/test_portfolio_model.py +++ b/tests/openbb_terminal/portfolio/test_portfolio_model.py @@ -2,18 +2,26 @@ # IMPORTATION THIRDPARTY import pandas as pd +from pathlib import Path # IMPORTATION INTERNAL from openbb_terminal.portfolio import portfolio_model -portfolio_trades = pd.read_csv("example_portfolio.csv") -portfolio_returns = pd.read_csv("portfolio_returns.csv") +def build_csv_path(csv_name: str): + folder_path = Path(__file__).parent + + return folder_path /"csv"/"test_portfolio_model"/csv_name + + +portfolio_trades = pd.read_csv(build_csv_path("example_portfolio.csv")) + +portfolio_returns = pd.read_csv(build_csv_path("portfolio_returns.csv")) portfolio_returns["Date"] = pd.to_datetime(portfolio_returns["Date"]) portfolio_returns = portfolio_returns.set_index("Date") -benchmark_returns = pd.read_csv("benchmark_returns.csv") +benchmark_returns = pd.read_csv(build_csv_path("benchmark_returns.csv")) benchmark_returns["Date"] = pd.to_datetime(benchmark_returns["Date"]) benchmark_returns = benchmark_returns.set_index("Date") From d06419521300a8dd2de7fd4baf8f22f990bb9862 Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Wed, 6 Jul 2022 23:12:30 +0200 Subject: [PATCH 23/24] Linting --- tests/openbb_terminal/portfolio/test_portfolio_model.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/openbb_terminal/portfolio/test_portfolio_model.py b/tests/openbb_terminal/portfolio/test_portfolio_model.py index 4479e86e9ec9..e82284f1a817 100644 --- a/tests/openbb_terminal/portfolio/test_portfolio_model.py +++ b/tests/openbb_terminal/portfolio/test_portfolio_model.py @@ -11,7 +11,7 @@ def build_csv_path(csv_name: str): folder_path = Path(__file__).parent - return folder_path /"csv"/"test_portfolio_model"/csv_name + return folder_path / "csv" / "test_portfolio_model" / csv_name portfolio_trades = pd.read_csv(build_csv_path("example_portfolio.csv")) From f97d37e9f548e6969ef87a880731699d1c9b92c2 Mon Sep 17 00:00:00 2001 From: northern-64bit <75195383+northern-64bit@users.noreply.github.com> Date: Wed, 6 Jul 2022 23:17:01 +0200 Subject: [PATCH 24/24] More linting --- tests/openbb_terminal/portfolio/test_portfolio_model.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/openbb_terminal/portfolio/test_portfolio_model.py b/tests/openbb_terminal/portfolio/test_portfolio_model.py index e82284f1a817..3100a790622f 100644 --- a/tests/openbb_terminal/portfolio/test_portfolio_model.py +++ b/tests/openbb_terminal/portfolio/test_portfolio_model.py @@ -1,8 +1,8 @@ # IMPORTATION STANDARD # IMPORTATION THIRDPARTY -import pandas as pd from pathlib import Path +import pandas as pd # IMPORTATION INTERNAL from openbb_terminal.portfolio import portfolio_model