| Overall Statistics |
|
Total Trades 25 Average Win 52.05% Average Loss -35.45% Compounding Annual Return 173.099% Drawdown 67.100% Expectancy 1.057 Net Profit 1323.339% Sharpe Ratio 2.365 Probabilistic Sharpe Ratio 80.195% Loss Rate 17% Win Rate 83% Profit-Loss Ratio 1.47 Alpha 1.418 Beta 0.004 Annual Standard Deviation 0.601 Annual Variance 0.361 Information Ratio 0.659 Tracking Error 0.857 Treynor Ratio 354.793 Total Fees $0.00 Estimated Strategy Capacity $15000000.00 Lowest Capacity Asset ETHUSD XJ |
class CalmAsparagusJackal(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2018, 10, 21)
#self.SetEndDate(2018, 7, 31)
self.SetCash(6418)
self.SetBenchmark(SecurityType.Crypto, "BTCUSD")
self.AddCrypto("BTCUSD", Resolution.Daily).Symbol
self.AddCrypto("ETHUSD", Resolution.Daily).Symbol
self.btcma = self.EMA("BTCUSD", 2, Resolution.Daily)
self.mama = self.EMA("ETHUSD", 2, Resolution.Daily)
self.baseline = self.ALMA("BTCUSD", 200, Resolution.Daily)
self.SetBenchmark("BTCUSD")
self.btcma.Updated += self.btcmaUpdated
self.btcWin = RollingWindow[IndicatorDataPoint](50)
self.mama.Updated += self.mamaUpdated
self.mamaWin = RollingWindow[IndicatorDataPoint](50)
self.SetWarmUp(600, Resolution.Hour)
def btcmaUpdated(self, sender, updated):
self.btcWin.Add(updated)
def mamaUpdated(self, sender, updated):
self.mamaWin.Add(updated)
def OnData(self, data):
if not self.baseline.IsReady:
return
bp1 = self.btcWin[49].Value
bp2 = self.btcWin[0].Value
mp1 = self.mamaWin[49].Value
mp2 = self.mamaWin[0].Value
btc_pct = ((bp2 - bp1)/bp1)
eth_pct = ((mp2 - mp1)/mp1)
dif_1 = eth_pct - btc_pct
dif_2 = btc_pct - eth_pct
if not self.Portfolio.Invested:
if self.Securities["BTCUSD"].Close > self.baseline.Current.Value*1.05:
if dif_1 >= .01:
self.SetHoldings("BTCUSD", 0)
self.SetHoldings("ETHUSD", 1)
elif dif_2 >= .01:
self.SetHoldings("ETHUSD", 0)
self.SetHoldings("BTCUSD", 1)
else: return
else: return
else:
if self.Securities["BTCUSD"].Close > self.baseline.Current.Value*.9:
if dif_1 >= .05:
self.SetHoldings("BTCUSD", 0)
self.SetHoldings("ETHUSD", 1)
elif dif_2 >= .05:
self.SetHoldings("ETHUSD", 0)
self.SetHoldings("BTCUSD", 1)
else: return
else: self.Liquidate()