Overall Statistics |
Total Orders 6 Average Win 0% Average Loss -0.69% Compounding Annual Return -6.004% Drawdown 3.900% Expectancy -1 Start Equity 100000 End Equity 97952.37 Net Profit -2.048% Sharpe Ratio -2.704 Sortino Ratio -1.883 Probabilistic Sharpe Ratio 6.051% Loss Rate 100% Win Rate 0% Profit-Loss Ratio 0 Alpha -0.136 Beta 0.155 Annual Standard Deviation 0.036 Annual Variance 0.001 Information Ratio -4.276 Tracking Error 0.082 Treynor Ratio -0.623 Total Fees $6.00 Estimated Strategy Capacity $900000000.00 Lowest Capacity Asset AAPL R735QTJ8XC9X Portfolio Turnover 0.96% |
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","TSLA"] 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, 0.2) self.entry_prices[symbol] = current_price # Exit condition elif current_price < supertrend1 and current_price < supertrend2: self.Liquidate(symbol) self.entry_prices[symbol] = None