Backtest

Overall Statistics
Total Orders 2372 Average Win 0.19% Average Loss -0.10% Compounding Annual Return 16.453% Drawdown 7.700% Expectancy 0.048 Start Equity 100000 End Equity 105294.47 Net Profit 5.294% Sharpe Ratio 0.523 Sortino Ratio 0.747 Probabilistic Sharpe Ratio 47.539% Loss Rate 65% Win Rate 35% Profit-Loss Ratio 2.01 Alpha -0.134 Beta 0.819 Annual Standard Deviation 0.124 Annual Variance 0.015 Information Ratio -1.767 Tracking Error 0.101 Treynor Ratio 0.079 Total Fees $4653.16 Estimated Strategy Capacity $490000.00 Lowest Capacity Asset BGU U7EC123NWZTX Portfolio Turnover 952.38%

from AlgorithmImports import *

class TopCryptoStrategy(QCAlgorithm):
    def Initialize(self):
        self.SetStartDate(2023, 12, 10)  # Set Start Date
        self.SetCash(100000)  # Set Strategy Cash

        # Define the symbols
        #self.crypto_symbols = []
        self.stock_symbols = ["AAPL","SPXL"]
        self.SetBenchmark("SPY")

        # Attempt to add each cryptocurrency and stock
        self.active_symbols = []
        '''for symbol in self.crypto_symbols:
            try:
                self.AddCrypto(symbol, Resolution.Daily)
                self.active_symbols.append(symbol)
            except Exception as e:
                self.Debug(f"Unable to add symbol: {symbol}. Exception: {e}")'''

        for symbol in self.stock_symbols:
            try:
                self.AddEquity(symbol, Resolution.MINUTE)
                self.active_symbols.append(symbol)
            except Exception as e:
                self.Debug(f"Unable to add symbol: {symbol}. Exception: {e}")

        # Define the technical indicators
        self.supertrend1 = {}
        self.supertrend2 = {}
        #self.rsi = {}
        #self.ema100 = {}
        #self.weekly_twap = {}
        self.entry_prices = {}

        for symbol in self.active_symbols:
            self.supertrend1[symbol] = self.STR(symbol, 10, 2.5, MovingAverageType.Wilders)
            self.supertrend2[symbol] = self.STR(symbol, 10, 3, MovingAverageType.Wilders)
            #self.rsi[symbol] = self.RSI(symbol, 10, MovingAverageType.Wilders, Resolution.Daily)
            #self.ema100[symbol] = self.EMA(symbol, 100, Resolution.Daily)
            #self.weekly_twap[symbol] = self.WeeklyTwap(symbol, 5)
            self.entry_prices[symbol] = None

        self.SetWarmUp(100, Resolution.MINUTE)  # Warm up period for 100 days

    def WeeklyTwap(self, symbol, num_weeks):
        twap = self.SMA(symbol, num_weeks * 5, Resolution.MINUTE)  # Assuming 5 trading days per week
        return twap

    def OnData(self, data):
        if self.IsWarmingUp:
            return

        for symbol in self.active_symbols:
            if not data.Bars.ContainsKey(symbol):
                continue

            bar = data.Bars[symbol]

            # Get current values
            current_price = bar.Close
            supertrend1 = self.supertrend1[symbol].Current.Value
            supertrend2 = self.supertrend2[symbol].Current.Value
            #rsi = self.rsi[symbol].Current.Value
            #ema100 = self.ema100[symbol].Current.Value
            #weekly_twap = self.weekly_twap[symbol].Current.Value

            # Define factor based on asset type
            #factor = 1.2 if symbol in self.crypto_symbols else 1.04

            # Entry condition
            if self.entry_prices[symbol] is None:
                if (current_price > supertrend1 and 
                    current_price > supertrend2 ):  # Use appropriate factor
                    self.Debug(f"{symbol}: Supertrend1={supertrend1}, Supertrend2={supertrend2}")
                    self.SetHoldings(symbol, 0.5)
                    self.entry_prices[symbol] = current_price

            # Exit condition
            elif current_price < supertrend1 and current_price < supertrend2:
                self.Liquidate(symbol)
                self.entry_prices[symbol] = None