from AlgorithmImports import *

class BTCUSDTrendFollowingAlgorithm(QCAlgorithm):
    def Initialize(self):
        # Extended backtest period
        self.SetStartDate(2020, 1, 1)  
        self.SetEndDate(2024, 1, 1)    
        self.SetCash(100000)           

        # Add BTC/USDC pair
        self.symbol = self.AddCrypto("BTCUSDC", Resolution.Daily).Symbol

        # Use a 10-day EMA
        self.ema = self.EMA(self.symbol, 10, Resolution.Daily)
        self.SetWarmUp(10, Resolution.Daily)  # Match warm-up to EMA period

        # Adjusted parameters
        self.stop_loss_percentage = 0.05  # 5% stop-loss
        self.allocation_percentage = 0.5  # 50% allocation

    def OnData(self, data):
        if not self.IsWarmingUp and data.ContainsKey(self.symbol):
            price = data[self.symbol].Close
            ema_value = self.ema.Current.Value

            # Enter trades when not invested
            if not self.Portfolio.Invested:
                if price > ema_value:  # Long
                    quantity = self.CalculateOrderQuantity(self.symbol, self.allocation_percentage)
                    self.MarketOrder(self.symbol, quantity)
                elif price < ema_value:  # Short
                    quantity = self.CalculateOrderQuantity(self.symbol, -self.allocation_percentage)
                    self.MarketOrder(self.symbol, quantity)
            # Manage existing trades
            else:
                holding = self.Portfolio[self.symbol]
                if holding.Invested:
                    if holding.Quantity > 0:  # Long
                        stop_price = holding.AveragePrice * (1 - self.stop_loss_percentage)
                        if price < stop_price:
                            self.Liquidate(self.symbol)
                    elif holding.Quantity < 0:  # Short
                        stop_price = holding.AveragePrice * (1 + self.stop_loss_percentage)
                        if price > stop_price:
                            self.Liquidate(self.symbol)