| Overall Statistics |
|
Total Trades 3732 Average Win 1.98% Average Loss -2.19% Compounding Annual Return 37.836% Drawdown 59.000% Expectancy 0.082 Net Profit 1011.165% Sharpe Ratio 0.947 Probabilistic Sharpe Ratio 24.509% Loss Rate 43% Win Rate 57% Profit-Loss Ratio 0.90 Alpha 0.435 Beta 0.226 Annual Standard Deviation 0.49 Annual Variance 0.24 Information Ratio 0.663 Tracking Error 0.503 Treynor Ratio 2.051 Total Fees $124489.18 Estimated Strategy Capacity $14000000.00 Lowest Capacity Asset TQQQ UK280CGTCB51 |
class VirtualRedDogfish(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2014, 1, 9)
self.SetCash(100000)
self.AddEquity("TQQQ", Resolution.Daily)
self.AddEquity("TMF", Resolution.Daily)
self.AddEquity("UVXY", Resolution.Daily)
self.vix = 'CBOE/VIX'
self.vxv = 'CBOE/VXV'
self.AddData(QuandlVix, self.vix, Resolution.Daily)
self.AddData(Quandl, self.vxv, Resolution.Daily)
self.vix_sma = self.SMA(self.vix, 1, Resolution.Daily)
self.vxv_sma = self.SMA(self.vxv, 1, Resolution.Daily)
self.ratio = IndicatorExtensions.Over(self.vxv_sma, self.vix_sma)
def OnData(self, data):
if not (self.vix_sma.IsReady and self.vxv_sma.IsReady and self.ratio.IsReady):
return
if self.ratio.Current.Value < .923:
self.SetHoldings("UVXY", .6)
self.Liquidate("TMF")
self.Liquidate("TQQQ")
self.SetHoldings("TQQQ", 0)
self.SetHoldings("TMF", 0)
else:
self.Liquidate("TQQQ")
self.Liquidate("TMF")
self.SetHoldings("TQQQ", .8)
self.SetHoldings("UVXY", 0)
self.SetHoldings("TMF", 0)
class QuandlVix(PythonQuandl):
def __init__(self):
self.ValueColumnName = "Close"