pnl_series_annual[symbol] = pnl_series[symbol].resample("Y").sum()
#pnl_series_annual[symbol]["DD"], *_ = pg.DD_sum(pnl_series_annual[symbol]["PNL"].cumsum(), 1)
#trades_table_csv = my_funcs.convert_datetime(trades_table)
#trades_table_csv.to_csv("Trade Data.csv", index=True)
#DD_distribution=pd.DataFrame(DD_distribution)
pnl_series = pd.DataFrame(pnl_series, index=universal_dates)
pnl_series.fillna(0, inplace=True)
pnl_series_monthly = pd.DataFrame(pnl_series_monthly, index=monthly_index)
pnl_series_monthly.fillna(0, inplace=True)
pnl_series_annual = pd.DataFrame(pnl_series_annual, index=annual_index)
pnl_series_annual.fillna(0, inplace=True)
#trades_table_csv.name = "trades_table_csv"
trade_summary_data.name = "trade_summary_data"
pnl_series.name = "pnl_series"
pnl_series_monthly.name = "pnl_series_monthly"
pnl_series_annual.name = "pnl_series_annual"
#DD_distribution.name = "DD_distribution"
to_be_saved_as_csv = [
trade_summary_data, pnl_series, pnl_series_monthly, pnl_series_annual
]
output_folder = system_name + "/" + underlying
#my_funcs.csv_creation(to_be_saved_as_csv, "Results/"+output_folder)
my_funcs.excel_creation(to_be_saved_as_csv, "Results/" + output_folder,
underlying)
cash_price_data = my_funcs.import_all_price_data_from_csv_files(
cash_data_folder_path)
cash_symbol_data_list = pd.Series(cash_price_data.keys())
futures_1_price_data = my_funcs.import_all_price_data_from_csv_files(
futures_1_data_folder_path)
futures_1_symbol_data_list = pd.Series(futures_1_price_data.keys())
expiry_days = pd.read_csv(expiry_days_path)
expiry_days = pd.to_datetime(expiry_days["Expiry days"])
expiry_days = expiry_days[expiry_days.between(portfolio_start_date,
portfolio_end_date)]
universe_stocks = pd.read_csv(universe_stocks_path)
buy_portfolio, sell_portfolio, daily_universe_portfolios, daily_universe = creating_portfolio(
cash_price_data, nifty_data, universe_stocks, expiry_days,
universal_dates)
buy_portfolio.name = "Buy Portfolio"
sell_portfolio.name = "Sell Portfolio"
daily_universe.name = "Daily Returns"
daily_universe_portfolios.name = "Daily Universe"
to_be_saved_as_file = [
buy_portfolio, sell_portfolio, daily_universe,
daily_universe_portfolios
]
my_funcs.excel_creation(to_be_saved_as_file, "Portfolio Results/DailyMR",
"DailyMR Results")
freq="Y")
cash_price_data = my_funcs.import_all_price_data_from_csv_files(
cash_data_folder_path)
cash_symbol_data_list = pd.Series(cash_price_data.keys())
futures_1_price_data = my_funcs.import_all_price_data_from_csv_files(
futures_1_data_folder_path)
futures_1_symbol_data_list = pd.Series(futures_1_price_data.keys())
expiry_days = pd.read_csv(expiry_days_path)
expiry_days = pd.to_datetime(expiry_days["Expiry days"])
expiry_days = expiry_days[expiry_days.between(portfolio_start_date,
portfolio_end_date)]
universe_stocks = pd.read_csv(universe_stocks_path)
buy_portfolio, sell_portfolio, monthly_universe_portfolios, RSC_universe = creating_portfolio(
cash_price_data, universe_stocks, expiry_days, universal_dates, 10)
buy_portfolio.name = "Buy Portfolio"
sell_portfolio.name = "Sell Portfolio"
RSC_universe.name = "RSC reversion"
monthly_universe_portfolios.name = "Monthly Universe"
to_be_saved_as_file = [
buy_portfolio, sell_portfolio, RSC_universe,
monthly_universe_portfolios
]
my_funcs.excel_creation(to_be_saved_as_file,
"Portfolio Results/RSC reversion", "RSC_Nifty")
index="Trade ID")
pnl_series_monthly = pd.DataFrame(columns=["PNL", "DD"])
pnl_series_annual = pd.DataFrame(columns=["PNL", "DD"])
pnl_series_monthly["PNL"] = pnl_series["Cumulative PNL%"].resample(
"M").sum()
pnl_series_monthly["DD"], *_ = pg.DD_sum(
pnl_series_monthly["PNL"].cumsum(), 1)
pnl_series_monthly["_rolling_12m"] = pnl_series_monthly["PNL"].rolling(
12).sum()
pnl_series_monthly["_rolling_12m"].fillna(0, inplace=True)
pnl_series_annual["PNL"] = pnl_series["Cumulative PNL%"].resample(
"Y").sum()
pnl_series_annual["DD"], *_ = pg.DD_sum(pnl_series_annual["PNL"].cumsum(),
1)
pnl_series_monthly.name = "Monthly PNL"
pnl_series.name = "PNL Series New"
DD_distribution.name = "DD Data"
trade_data.name = "Sample Trade Data"
to_be_saved_as_csv = [
pnl_series_monthly, pnl_series, DD_distribution, trade_data
]
my_funcs.excel_creation(to_be_saved_as_csv, underlying_name, "trial.xlsx")
my_funcs.csv_creation(to_be_saved_as_csv, underlying_name)
trade_register = creating_individual_trade_db.creating_individual_trade_db(
trade_list_to_pass)
pnl_series_1, _ = pg.pnl_timeseries_multiple_strategy_trade(
trade_register, price_data, universal_dates, baseamount)
pnl_series_strategy[strategy] = pnl_series_1["Daily PNL"]
gross_exposure_strategy[strategy] = pnl_series_1["Gross Exposure"]
net_exposure_strategy[strategy] = pnl_series_1["EOD Net Exposure"]
pnl_series_strategy["Total"] = pnl_series_strategy.sum(axis=1)
pnl_series_strategy.loc["Total"] = pnl_series_strategy.sum(axis=0)
gross_exposure_strategy["Total"] = gross_exposure_strategy.sum(axis=1)
net_exposure_strategy["Total"] = net_exposure_strategy.sum(axis=1)
pnl_series[account] = [
pnl_series_strategy, gross_exposure_strategy, net_exposure_strategy
]
for account in account_list:
pnl_series[account][0].name = "PNL Series " + account
pnl_series[account][1].name = "Gross exposure Series " + account
pnl_series[account][2].name = "Net exposure Series " + account
to_be_saved_as_csv = [
pnl_series[account][0], pnl_series[account][1],
pnl_series[account][2]
]
my_funcs.excel_creation(to_be_saved_as_csv, "Pro_Alpha_PNL", account)
cash_symbol_data_list = pd.Series(cash_price_data.keys())
futures_1_price_data = my_funcs.import_all_price_data_from_csv_files(
futures_1_data_folder_path)
futures_1_symbol_data_list = pd.Series(futures_1_price_data.keys())
expiry_days = pd.read_csv(expiry_days_path)
expiry_days = pd.to_datetime(expiry_days["Expiry days"])
expiry_days = expiry_days[expiry_days.between(portfolio_start_date,
portfolio_end_date)]
universe_stocks = pd.read_csv(universe_stocks_path)
buy_portfolio, sell_portfolio, monthly_universe_portfolios, RSI_universe = creating_portfolio(
cash_price_data,
universe_stocks,
expiry_days,
universal_dates,
period=90)
buy_portfolio.name = "Buy Portfolio"
sell_portfolio.name = "Sell Portfolio"
RSI_universe.name = "D90_vol"
monthly_universe_portfolios.name = "Monthly Universe"
to_be_saved_as_file = [
buy_portfolio, sell_portfolio, RSI_universe,
monthly_universe_portfolios
]
my_funcs.excel_creation(to_be_saved_as_file, "Portfolio Results/D90_Vol",
"D90_volatility_Nifty")
pnl_series_monthly_rolling_12m = pnl_series_monthly["PNL"].rolling(
12).sum()
pnl_series_monthly_rolling_12m.fillna(0, inplace=True)
pnl_series_annual["PNL"] = pnl_series["%PNL"].resample("Y").sum()
pnl_series_annual["DD"], *_ = pg.DD_sum(pnl_series_annual["PNL"].cumsum(),
1)
trades_table_csv = my_funcs.convert_datetime(trades_table)
price_signal.name = "price_signal"
trades_table_csv.name = "trades_table"
trade_summary_data.name = "trade_summary_data"
pnl_series.name = "pnl_series"
pnl_series_monthly.name = "pnl_series_monthly"
pnl_series_annual.name = "pnl_series_annual"
DD_distribution.name = "DD_distribution"
trades_12m_rolling_summary.name = "Rolling 12 month analysis"
walk_forward_annual_summary.name = "Walk forward analysis"
Dataframes_to_be_saved_as_csv = [
price_signal, trades_table, trade_summary_data, pnl_series,
pnl_series_monthly, pnl_series_annual, DD_distribution,
trades_12m_rolling_summary, walk_forward_annual_summary
]
#my_funcs.csv_creation(Dataframes_to_be_saved_as_csv, underlying_name)
my_funcs.excel_creation(Dataframes_to_be_saved_as_csv, underlying_name,
symbol)
cash_price_data = my_funcs.import_all_price_data_from_csv_files(
cash_data_folder_path)
cash_symbol_data_list = pd.Series(cash_price_data.keys())
futures_1_price_data = my_funcs.import_all_price_data_from_csv_files(
futures_1_data_folder_path)
futures_1_symbol_data_list = pd.Series(futures_1_price_data.keys())
expiry_days = pd.read_csv(expiry_days_path)
expiry_days = pd.to_datetime(expiry_days["Expiry days"])
expiry_days = expiry_days[expiry_days.between(portfolio_start_date,
portfolio_end_date)]
universe_stocks = pd.read_csv(universe_stocks_path)
buy_portfolio, sell_portfolio, monthly_universe_portfolios, sign_momentum_universe = creating_portfolio(
cash_price_data, universe_stocks, expiry_days, universal_dates)
buy_portfolio.name = "Buy Portfolio"
sell_portfolio.name = "Sell Portfolio"
sign_momentum_universe.name = "sign momentum returns"
monthly_universe_portfolios.name = "Monthly Universe"
to_be_saved_as_file = [
buy_portfolio, sell_portfolio, sign_momentum_universe,
monthly_universe_portfolios
]
my_funcs.excel_creation(to_be_saved_as_file,
"Portfolio Results/sign Momentum",
"sign_Momentum_Nifty")
universal_dates[-1],
freq="Y")
cash_price_data = my_funcs.import_all_price_data_from_csv_files(
cash_data_folder_path)
cash_symbol_data_list = pd.Series(cash_price_data.keys())
futures_1_price_data = my_funcs.import_all_price_data_from_csv_files(
futures_1_data_folder_path)
futures_1_symbol_data_list = pd.Series(futures_1_price_data.keys())
expiry_days = pd.read_csv(expiry_days_path)
expiry_days = pd.to_datetime(expiry_days["Expiry days"])
expiry_days = expiry_days[expiry_days.between(portfolio_start_date,
portfolio_end_date)]
universe_stocks = pd.read_csv(universe_stocks_path)
universe_sector_data = pd.read_csv(universe_sector_path)
sectors = ["IT", "Energy", "Financial", "Pharma", "Consumer"]
buy_portfolio, sell_portfolio = creating_portfolio(
cash_price_data, nifty_data, universe_stocks, expiry_days,
universal_dates, universe_sector_data, sectors)
buy_portfolio.name = "Buy Portfolio"
sell_portfolio.name = "Sell Portfolio"
to_be_saved_as_file = [buy_portfolio, sell_portfolio]
my_funcs.excel_creation(to_be_saved_as_file,
"Portfolio Results/Sector Neutral",
"Sector Neutral Results")