Overall Statistics |
Total Trades 4780 Average Win 0.47% Average Loss -0.81% Compounding Annual Return 278.327% Drawdown 63.100% Expectancy 0.383 Net Profit 102061.376% Sharpe Ratio 3.229 Probabilistic Sharpe Ratio 98.161% Loss Rate 12% Win Rate 88% Profit-Loss Ratio 0.58 Alpha 2.055 Beta 0.303 Annual Standard Deviation 0.648 Annual Variance 0.421 Information Ratio 2.996 Tracking Error 0.656 Treynor Ratio 6.903 Total Fees $66148048.35 Estimated Strategy Capacity $230000.00 Lowest Capacity Asset ETHUSD XJ |
class AnalyticCryptoAlgo(QCAlgorithm): def Initialize(self): self.SetStartDate(2016, 5, 2) self.SetCash(1000000) self.AddEquity("SPY", Resolution.Minute) self.SetBenchmark("SPY") self.SetBrokerageModel(BrokerageName.AlphaStreams) self.SetExecution(ImmediateExecutionModel()) self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel()) symbol_list = ["BTCUSD","ETHUSD","LTCUSD","BALUSD","DAIUSD","KNCUSD","OXTUSD"] symbols = [self.AddCrypto(symbol, Resolution.Minute, Market.GDAX).Symbol for symbol in symbol_list] self.AddAlpha(AnalyticCryptoAlphaModel(self.Time)) class AnalyticCryptoAlphaModel(AlphaModel): def __init__(self, Time): self.dataBySymbol = {} self.rebalanceTime = Time def Update(self, algorithm, data): insights = [] if algorithm.Time < self.rebalanceTime: return [] for symbol, symbolData in self.dataBySymbol.items(): if data.Bars.ContainsKey(symbol) and symbolData.IsReady(): if symbolData.slow.Current.Value < symbolData.fast.Current.Value: insights.append(Insight(symbol, timedelta(days=30), InsightType.Price, InsightDirection.Up)) else: insights.append(Insight(symbol, timedelta(days=30), InsightType.Price, InsightDirection.Flat)) self.rebalanceTime = Expiry.EndOfDay(algorithm.Time) return insights def OnSecuritiesChanged(self, algorithm, changes): for change in changes.AddedSecurities: self.dataBySymbol[change.Symbol] = SymbolData(algorithm, change.Symbol) for change in changes.RemovedSecurities: if change.Symbol in self.dataBySymbol: del self.dataBySymbol[change.Symbol] class SymbolData: def __init__(self, algorithm, symbol): algorithm.Consolidate(symbol, Resolution.Daily, self.DailyBarHandler) self.fast = algorithm.SMA(symbol, 5, Resolution.Daily, Field.Low) self.slow = algorithm.SMA(symbol, 60, Resolution.Daily, Field.High) history = algorithm.History(symbol, 60, Resolution.Daily) if not history.empty: for index, tradebar in history.loc[symbol].iterrows(): self.fast.Update(index, tradebar.low) self.slow.Update(index, tradebar.high) last_row = history.loc[symbol].iloc[-1] self.open = last_row.open self.close = last_row.close self.high = last_row.high self.low = last_row.low def DailyBarHandler(self, consolidated): self.open = consolidated.Open self.close = consolidated.Close self.high = consolidated.High self.low = consolidated.Low def IsReady(self): return self.fast.IsReady and self.slow.IsReady