| 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