Create calculator2.py

utils/calculator2.py

@@ -0,0 +1,44 @@
+import pandas as pd
+
+def simulate_all_in_trading(signals_data):
+    """
+    Simulates trading by going all-in on the first buy signal and selling all on the first sell signal,
+    then repeating the process with the new amount of cash including profit or loss.
+    
+    Parameters:
+    - signals_data (pd.DataFrame): DataFrame with 'Close', 'Buy_Signal', and 'Sell_Signal'.
+    
+    Returns:
+    - float: The final amount of cash after applying the trading strategy.
+    - int: The number of trades executed.
+    """
+    cash = 1000  # Initial cash
+    holding = False
+    trades_executed = 0
+
+    for index, row in signals_data.iterrows():
+        if not holding and row['Buy_Signal']:
+            # Buy all you can with the available cash
+            shares = cash / row['Close']
+            holding = True
+            trades_executed += 1
+
+        elif holding and row['Sell_Signal']:
+            # Sell all shares
+            cash = shares * row['Close']
+            holding = False
+            trades_executed += 1
+
+    return cash, trades_executed
+
+if __name__ == "__main__":
+    # Example DataFrame with close prices and buy/sell signals
+    signals_data = pd.DataFrame({
+        'Close': [100, 105, 103, 108, 107, 110, 108, 112],  # Example close prices
+        'Buy_Signal': [False, True, False, False, True, False, False, False],
+        'Sell_Signal': [False, False, True, False, False, True, False, False]
+    })
+
+    final_cash, trades = simulate_all_in_trading(signals_data)
+    print(f"Final Cash: ${final_cash:.2f}")
+    print(f"Trades Executed: {trades}")