utils/calculator.py

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}")