| Overall Statistics |
|
Total Trades 5464 Average Win 0.39% Average Loss -0.72% Compounding Annual Return 175.960% Drawdown 88.200% Expectancy 0.294 Net Profit 19615.711% Sharpe Ratio 2.279 Probabilistic Sharpe Ratio 86.241% Loss Rate 16% Win Rate 84% Profit-Loss Ratio 0.55 Alpha 1.463 Beta 0.389 Annual Standard Deviation 0.664 Annual Variance 0.441 Information Ratio 2.07 Tracking Error 0.668 Treynor Ratio 3.89 Total Fees $16605932.31 Estimated Strategy Capacity $830000.00 Lowest Capacity Asset ETHUSD XJ |
class StatArbAlgo(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2016, 5, 2)
self.SetEndDate(2021, 7, 14)
self.SetCash(1000000)
self.AddEquity("SPY", Resolution.Minute)
self.SetBenchmark("SPY")
self.SetBrokerageModel(BrokerageName.AlphaStreams)
self.SetExecution(ImmediateExecutionModel())
self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel())
symbols = [self.AddCrypto(symbol, Resolution.Minute).Symbol for symbol in ["BTCUSD","ETHUSD","LTCUSD"]]
self.AddAlpha(StatArbAlphaModel(self.Time))
class StatArbAlphaModel(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.Low)
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.low)
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