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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}")
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