Overall Statistics |
Total Trades 1753 Average Win 2.97% Average Loss -1.14% Compounding Annual Return 75.384% Drawdown 30.200% Expectancy 0.351 Net Profit 1723.438% Sharpe Ratio 1.515 Loss Rate 62% Win Rate 38% Profit-Loss Ratio 2.60 Alpha -0.017 Beta 33.335 Annual Standard Deviation 0.426 Annual Variance 0.182 Information Ratio 1.469 Tracking Error 0.426 Treynor Ratio 0.019 Total Fees $35436.93 |
from System import * from QuantConnect import * from QuantConnect.Algorithm import * from QuantConnect.Data import * import numpy as np from datetime import timedelta """ I have UVXY set to the variable self.vxx. I was too lazy to change all of the variables from self.vxx to self.uvxy. """ class BasicTemplateAlgorithm(QCAlgorithm): def Initialize(self): # Set the cash we'd like to use for our backtest # This is ignored in live trading self.SetCash(37000) # Set benchmark self.SetBenchmark("XIV") # Start and end dates for the backtest. # These are ignored in live trading. self.SetStartDate(2013,06,8) self.SetEndDate(2018,1,19) #Assets predetermined self.vxx = self.AddEquity("UVXY", Resolution.Hour).Symbol self.xiv = self.AddEquity("XIV", Resolution.Hour).Symbol self.spy = self.AddEquity("SPY", Resolution.Hour).Symbol # Indicators self.emaBig = self.EMA("XIV", 5, Resolution.Hour) self.emaSmall = self.EMA("XIV", 2, Resolution.Hour) self.smaBig = self.SMA("SPY", 200, Resolution.Hour) self.smaSmall = self.SMA("SPY", 100, Resolution.Hour) self.emaBullBIG = self.EMA("SPY", 50, Resolution.Hour) self.emaBullSMALL = self.EMA("SPY", 25, Resolution.Hour) # Schedules self.Schedule.On(self.DateRules.EveryDay(), self.TimeRules.Every(timedelta(minutes=5)), Action(self.LiquidateUnrealizedLosses)) self.Schedule.On(self.DateRules.EveryDay("SPY"), self.TimeRules.AfterMarketOpen("SPY", 4), Action(self.EveryDayAfterMarketOpen)) # schedule an event to fire every trading day for a security the # time rule here tells it to fire 10 minutes before SPY's market close self.Schedule.On(self.DateRules.EveryDay("SPY"), self.TimeRules.BeforeMarketClose("SPY", 10), Action(self.EveryDayBeforeMarketClose)) # Timer self.t = 0 # Unrealized earnings total for each day. Pi stands for percent increase. self.pi = 0 # Timer that is switched to 1 if the market is 10 minutes from closing. self.closing = 0 # Get warmup data so that the Algorithm can start trading self.SetWarmUp(timedelta(200)) def OnData(self, slice): if self.t == 0: if self.t == 0: if self.smaBig < self.smaSmall: if not self.Portfolio.Invested: if self.emaBig < self.emaSmall: self.SetHoldings(self.xiv, 0.75) self.SetHoldings(self.vxx, 0) elif self.Portfolio.Invested: if self.emaBig > self.emaSmall: self.SetHoldings(self.xiv, 0) self.SetHoldings(self.vxx, 0) # If the market is detected to be in a downward trend, a whole new set of Indicators are used elif self.smaBig > self.smaSmall: if self.emaBullBIG < self.emaBullSMALL: if not self.Portfolio.Invested: if self.emaBig < self.emaSmall: self.SetHoldings(self.xiv, 0.75) self.SetHoldings(self.vxx, 0) elif self.Portfolio['XIV'].Quantity > 0: if self.emaBig > self.emaSmall: self.SetHoldings(self.xiv, 0) self.SetHoldings(self.vxx, 0.375) elif self.Portfolio['UVXY'].Quantity > 0: if self.emaBig < self.emaSmall: self.SetHoldings(self.xiv, 0.75) self.SetHoldings(self.vxx, 0) elif self.emaBullBIG > self.emaBullSMALL: if not self.Portfolio.Invested: #Buy XIV if EMA 3 is > EMA 9 if self.emaBig < self.emaSmall: self.SetHoldings(self.xiv, 0.75) self.SetHoldings(self.vxx, 0) elif self.Portfolio['XIV'].Quantity > 0: if self.emaBig > self.emaSmall: self.SetHoldings(self.xiv, 0) self.SetHoldings(self.vxx, 0.75) elif self.Portfolio['UVXY'].Quantity > 0: if self.emaBig < self.emaSmall: self.SetHoldings(self.xiv, 0.75) self.SetHoldings(self.vxx, 0) """ THIS IS THE FUNCTION THAT IS CHANGIGN RETURNS """ def LiquidateUnrealizedLosses(self): pass # This function sets t back to 0 every day 10 minutes after the market opens def EveryDayAfterMarketOpen(self): self.t = 0 self.pi = 0 self.closing = 0 def EveryDayBeforeMarketClose(self): self.closing = 1