| Overall Statistics |
|
Total Trades 133 Average Win 0.93% Average Loss -0.63% Compounding Annual Return 11.702% Drawdown 13.400% Expectancy 0.678 Net Profit 39.418% Sharpe Ratio 0.925 Probabilistic Sharpe Ratio 41.273% Loss Rate 32% Win Rate 68% Profit-Loss Ratio 1.48 Alpha 0.043 Beta 0.36 Annual Standard Deviation 0.091 Annual Variance 0.008 Information Ratio -0.227 Tracking Error 0.135 Treynor Ratio 0.233 Total Fees $298.54 Estimated Strategy Capacity $69000000.00 Lowest Capacity Asset BND TRO5ZARLX6JP |
class FormalBlueCaterpillar(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2018, 1, 1)
self.SetEndDate(2021, 1, 1)
self.SetCash(100000)
self.spy = self.AddEquity("SPY", Resolution.Daily).Symbol
self.bnd = self.AddEquity("BND", Resolution.Daily).Symbol
self.sma = self.SMA(self.spy, 30, Resolution.Daily)
self.rebalancetime = datetime.min
self.uptrend = True
def OnData(self, data):
if not self.sma.IsReady or self.spy not in data or self.bnd not in data:
return
if data[self.spy].Price >= self.sma.Current.Value:
if self.Time >= self.rebalancetime or not self.uptrend:
self.SetHoldings(self.spy, 0.8)
self.SetHoldings(self.bnd, 0.2)
self.uptrend = True
self.rebalancetime = self.Time + timedelta(30)
elif self.Time >= self.rebalancetime or self.uptrend: #Check ob es Zeit für Rebalance ist oder ob wir vorher in einem Uptrend waren
self.SetHoldings(self.spy, 0.2)
self.SetHoldings(self.bnd, 0.8)
self.uptrend = False
self.rebalancetime = self.Time + timedelta(30)
self.Plot("Benchmark", "SMA", self.sma.Current.Value)