Formulation_backtesting.py

# Trading strategy formulation and backtesting
def backtest_strategy(final_data, initial_capital=10000, capital_deployed=0.2):
    trade_log = []
    for i in range(len(final_data) - 5):
        prediction = final_data.iloc[i]['Predictions']
        if prediction == 0 or np.isnan(prediction):
            continue


        direction = 'Long' if prediction > 0 else 'Short'
        entry_price = final_data.iloc[i + 1]['Open']
        exit_price = final_data.iloc[i + 5]['Close']


        trade_return = (exit_price - entry_price) / entry_price if direction == 'Long' else (entry_price - exit_price) / entry_price
        capital_change = capital_deployed * trade_return


        trade_log.append({
            'Signal_Day': i,
            'Entry_Day': i + 1,
            'Exit_Day': i + 5,
            'Direction': direction,
            'Entry_Price': entry_price,
            'Exit_Price': exit_price,
            'Return': trade_return,
            'Capital_Change': capital_change
        })


    return pd.DataFrame(trade_log)