analysis.py

import pandas as pd

def run():
    csv_file = 'backtest_results/AAPL+MSFT+NVDA+SPY+QQQ+TSLA+AMD+GOOG+META+AMZN+JPM+GS+V+JNJ+PFE+UNH+XOM+CVX+WMT+KO+CAT+GE+DIS+NFLX+IWM_2026-03-09_2026-04-13_trades.csv'
    df = pd.read_csv(csv_file)
    
    print("Exit Reason Analysis")
    print("-" * 40)
    
    time_stops = df[df['exit_reason'] == 'time_stop']
    stop_losses = df[df['exit_reason'] == 'stop_loss']
    take_profits = df[df['exit_reason'] == 'take_profit']
    
    print(f"Time Stops: {len(time_stops)} trades, Average PnL: ${time_stops['pnl'].mean():.2f}")
    
    if len(stop_losses) > 0:
        print(f"Stop Losses: {len(stop_losses)} trades, Average PnL: ${stop_losses['pnl'].mean():.2f}")
    else:
        print("Stop Losses: 0 trades")
        
    if len(take_profits) > 0:
        print(f"Take Profits: {len(take_profits)} trades, Average PnL: ${take_profits['pnl'].mean():.2f}")
    else:
        print("Take Profits: 0 trades")
        
    print("\nImpact of Lower TP (2.0R vs 3.0-3.5R):")
    print("A lower take profit (e.g., 2.0R) would likely increase the win rate by closing trades earlier, but would reduce the average win size.")
    print("This could be beneficial for a smaller account ($300) to ensure faster equity turnover and reduce time-in-market risk.")

if __name__ == "__main__":
    run()