def simulate_trading(signals_data, initial_capital=1000, investment_per_buy=100): """ Simulates trading based on buy and sell signals. Parameters: - signals_data (pd.DataFrame): DataFrame with 'Close', 'Buy_Signal', and 'Sell_Signal'. - initial_capital (float): The initial capital at the start of the trading period. - investment_per_buy (float): The fixed amount in dollars to invest at each buy signal. Returns: - float: The value of the stock currently held at the end of the period. - float: The amount of cash remaining if any. """ cash = initial_capital holdings = 0 for _, row in signals_data.iterrows(): # Buy if row['Buy_Signal'] and cash >= investment_per_buy: shares_bought = investment_per_buy / row['Close'] holdings += shares_bought cash -= investment_per_buy # Sell if row['Sell_Signal'] and holdings > 0: shares_sold = holdings * 0.25 holdings -= shares_sold cash += shares_sold * row['Close'] # Calculate the value of the remaining stock holdings at the last known price final_stock_value = holdings * signals_data.iloc[-1]['Close'] return final_stock_value, cash # Example usage if __name__ == "__main__": # Assuming signals_data DataFrame exists with 'Close', 'Buy_Signal', 'Sell_Signal' signals_data = pd.DataFrame({ 'Close': [100, 105, 103, 108, 107], # Example close prices 'Buy_Signal': [True, False, True, False, False], 'Sell_Signal': [False, True, False, True, False] }, index=pd.date_range(start='2020-01-01', periods=5, freq='D')) final_stock_value, remaining_cash = simulate_trading(signals_data) print(f"Final Value of Stock Holdings: ${final_stock_value:.2f}") print(f"Remaining Cash: ${remaining_cash:.2f}")