Overall Statistics |
Total Orders 2 Average Win 34.02% Average Loss 0% Compounding Annual Return 115.795% Drawdown 7.600% Expectancy 0 Start Equity 100000 End Equity 134020.81 Net Profit 34.021% Sharpe Ratio 2.711 Sortino Ratio 3.292 Probabilistic Sharpe Ratio 80.603% Loss Rate 0% Win Rate 100% Profit-Loss Ratio 0 Alpha 0.297 Beta 2.512 Annual Standard Deviation 0.262 Annual Variance 0.069 Information Ratio 2.996 Tracking Error 0.182 Treynor Ratio 0.283 Total Fees $10.53 Estimated Strategy Capacity $26000000.00 Lowest Capacity Asset BGU U7EC123NWZTX Portfolio Turnover 1.42% |
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 = ["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.Daily) 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.Daily) # Warm up period for 100 days def WeeklyTwap(self, symbol, num_weeks): twap = self.SMA(symbol, num_weeks * 5, Resolution.Daily) # 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, 1) self.entry_prices[symbol] = current_price # Exit condition elif current_price < supertrend1 and current_price < supertrend2: self.Liquidate(symbol) self.entry_prices[symbol] = None