Create Range.py

Author: SL-Mar

Strategies/Range.py

@@ -0,0 +1,74 @@
+#AI generated code extracted from Sapate, Uttam B, Trading Range Breakout Test on Daily Stocks of Indian Markets (November 10, 2017). 
+#Available at SSRN: https://ssrn.com/abstract=3068852 or http://dx.doi.org/10.2139/ssrn.3068852 
+
+from AlgorithmImports import *
+
+class MyTradingAlgorithm(QCAlgorithm):
+    def Initialize(self):
+        # Set the start and end date for backtesting
+        self.SetStartDate(2024, 1, 1)
+        self.SetEndDate(2024, 12, 1)
+        
+        # Set the initial cash balance
+        self.SetCash(100000)
+        
+        # Add the assets to trade
+        self.symbols = [self.AddEquity("SPY", Resolution.Daily).Symbol,
+                        self.AddEquity("AAPL", Resolution.Daily).Symbol]
+        
+        # Set the benchmark
+        self.SetBenchmark("SPY")
+        
+        # Initialize indicators
+        self.sma_short = {symbol: self.SMA(symbol, 50, Resolution.Daily) for symbol in self.symbols}
+        self.sma_long = {symbol: self.SMA(symbol, 200, Resolution.Daily) for symbol in self.symbols}
+        
+        # Initialize risk management parameters
+        self.stop_loss_pct = 0.05
+        self.trailing_stop_pct = 0.02
+        
+        # Initialize portfolio construction parameters
+        self.max_position_size = 0.5  # Max 50% of portfolio in one position
+        
+        # Schedule the rebalancing function
+        self.Schedule.On(self.DateRules.MonthStart(), self.TimeRules.AfterMarketOpen("SPY", 30), self.Rebalance)
+        
+    def OnData(self, data):
+        for symbol in self.symbols:
+            if not data.ContainsKey(symbol):
+                continue
+            
+            # Check if indicators are ready
+            if not self.sma_short[symbol].IsReady or not self.sma_long[symbol].IsReady:
+                continue
+            
+            # Strategy logic: Golden Cross
+            if self.sma_short[symbol].Current.Value > self.sma_long[symbol].Current.Value:
+                self.SetHoldings(symbol, self.max_position_size)
+            else:
+                self.Liquidate(symbol)
+            
+            # Risk management: Trailing stop loss
+            if self.Portfolio[symbol].Invested:
+                self.SetTrailingStopLoss(symbol, self.trailing_stop_pct)
+    
+    def Rebalance(self):
+        # Rebalance the portfolio
+        for symbol in self.symbols:
+            self.SetHoldings(symbol, self.max_position_size)
+    
+    def SetTrailingStopLoss(self, symbol, trailing_stop_pct):
+        # Set a trailing stop loss for the given symbol
+        if self.Portfolio[symbol].Invested:
+            stop_price = self.Portfolio[symbol].Price * (1 - trailing_stop_pct)
+            self.StopMarketOrder(symbol, -self.Portfolio[symbol].Quantity, stop_price)
+    
+    def OnOrderEvent(self, orderEvent):
+        # Log order events for debugging
+        self.Debug(f"Order event: {orderEvent}")
+    
+    def OnEndOfAlgorithm(self):
+        # Log final portfolio value
+        self.Debug(f"Final Portfolio Value: {self.Portfolio.TotalPortfolioValue}")
+
+# Helper functions can be added here if needed