folder_path = Path().absolute().joinpath("Data/Stock prices CSV")
nifty_path = Path().absolute().joinpath("Data/price_Data/Nifty Index.csv")
nifty_data = my_funcs.reading_price_data_from_csv(nifty_path)
universal_dates = nifty_data.index
monthly_index = pd.date_range(universal_dates[0],
universal_dates[-1],
freq="M")
annual_index = pd.date_range(universal_dates[0],
universal_dates[-1],
freq="Y")
price_data = my_funcs.import_all_price_data_from_csv_files(folder_path)
symbols = price_data.keys()
initial_capital = 1000000
trading_cost = 0.0000
trade_summary_data = pd.DataFrame(columns=[
"Total Trades", "Profit Factor", "Total Profit", "Average Profit",
"Max Profit", "Min Profit", "Average Duration", "Hit Ratio",
"Profitability", "Max DD in Trade", "Max Profit in Trade",
"Max Loss in Trade", "Max Recovery in Trade",
"Max DD Duration in Trade"
])
trades_table = {}
trades_12m_rolling_summary = {}
portfolio_start_date = datetime.datetime(2010, 12, 1)
portfolio_end_date = datetime.datetime(2022, 2, 28)
nifty_data = my_funcs.reading_price_data_from_csv(nifty_price_data_path)
universal_dates = nifty_data.index[
(nifty_data.index > portfolio_start_date)
& (nifty_data.index <= portfolio_end_date)]
monthly_index = pd.date_range(universal_dates[0],
universal_dates[-1],
freq="M")
annual_index = pd.date_range(universal_dates[0],
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)
buy_portfolio, sell_portfolio, daily_universe_portfolios, daily_universe = creating_portfolio(
cash_price_data, nifty_data, universe_stocks, expiry_days,
universal_dates)
portfolio_strategy = "SML"
current_folder_path = Path().absolute().joinpath("Data")
data_folder_path_cash = Path().absolute().joinpath("Data/Cash prices CSV")
data_folder_path_futures2 = Path().absolute().joinpath(
"Data/New Futures prices series2 CSV")
nifty_price_data_path = Path().absolute().joinpath(
"Data/Price_Data/Nz1 Index.csv")
expiry_days_path = current_folder_path / "Expiry days.csv"
buy_trade_file = current_folder_path / "Portfolio_construction/SML/SML_buy_trades.csv"
sell_trade_file = current_folder_path / "Portfolio_construction/SML/SML_sell_trades.csv"
nifty_data = my_funcs.reading_price_data_from_csv(nifty_price_data_path)
universal_dates = nifty_data.index
price_data = my_funcs.import_all_price_data_from_csv_files(
data_folder_path_cash)
price_data_futures2 = my_funcs.import_all_price_data_from_csv_files(
data_folder_path_futures2)
symbols_data = price_data.keys()
monthly_index = pd.date_range(universal_dates[0],
universal_dates[-1],
freq="M")
annual_index = pd.date_range(universal_dates[0],
universal_dates[-1],
freq="Y")
buy_trades = pd.read_csv(buy_trade_file)
buy_trades.set_index("Dates", inplace=True)
buy_trades.index = pd.to_datetime(buy_trades.index)