| Overall Statistics |
|
Total Trades 15 Average Win 2.46% Average Loss -0.65% Compounding Annual Return 279.570% Drawdown 4.100% Expectancy 1.052 Net Profit 4.658% Sharpe Ratio 4.114 Probabilistic Sharpe Ratio 73.171% Loss Rate 57% Win Rate 43% Profit-Loss Ratio 3.79 Alpha 0.851 Beta -0.247 Annual Standard Deviation 0.239 Annual Variance 0.057 Information Ratio 3.697 Tracking Error 0.412 Treynor Ratio -3.992 Total Fees $29.31 |
import numpy as np
### <summary>
### Basic template algorithm simply initializes the date range and cash. This is a skeleton
### framework you can use for designing an algorithm.
### </summary>
class BasicTemplateAlgorithm(QCAlgorithm):
'''Basic template algorithm simply initializes the date range and cash'''
def Initialize(self):
self.SetStartDate(2019, 12, 1) #Set Start Date
self.SetEndDate(datetime.now().date() - timedelta(1)) # Set End Date
self.SetCash(10000) #Set Strategy Cash
self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage) # Set Brokerage Model
self.SetTimeZone("America/New_York") # Set Time Zone
# Find more symbols here: http://quantconnect.com/data
self.svxy = self.AddEquity("SVXY", Resolution.Minute)
self.svxy.SetDataNormalizationMode(DataNormalizationMode.Raw) # Select Normalization Mode
self.vxz = self.AddEquity("VXZ", Resolution.Minute)
self.vxz.SetDataNormalizationMode(DataNormalizationMode.Raw) # Select Normalization Mode
self.fast = self.RSI("SVXY", 6, MovingAverageType.Simple, Resolution.Hour) # define a period RSI indicator
#self.slow = self.RSI("SVXY", 15, MovingAverageType.Simple, Resolution.Hour) # define a period RSI indicator
self.previous = None
self.SetBenchmark("SVXY") # Set Benchmark
self.SetWarmUp(20, Resolution.Hour) # Set Warm Up
for m in range (29,330,60): # 9:59 AM - 2:59 PM
self.Schedule.On(self.DateRules.EveryDay("SVXY"), self.TimeRules.AfterMarketOpen("SVXY", minutes=m), Action(self.OnDataCopy))
#self.Schedule.On(self.DateRules.EveryDay(), self.TimeRules.AfterMarketOpen("SVXY", 29), Action(self.Open)) #9:59 AM
self.Schedule.On(self.DateRules.EveryDay(), self.TimeRules.BeforeMarketClose("SVXY", 1), Action(self.OnDataCopy)) #3:59 PM
def OnData(self, data):
pass
def OnDataCopy(self):
if self.IsWarmingUp: # Don't place trades until our indicators are warmed up
return
holdingsSVXY = self.Portfolio["SVXY"].Quantity
holdingsVXZ = self.Portfolio["VXZ"].Quantity
# when fastRSI above 50, buy SVXY & sell VXZ
#if holdingsSVXY <= 0:
if self.fast.Current.Value > 50: # when RSIfast above 50, sell VXZ & buy SVXY
self.Liquidate("VXZ")
self.Debug(str(self.Portfolio["VXZ"].AveragePrice)) # Debug average price
self.SetHoldings("SVXY", 1.0, True)
self.Debug(str(self.Portfolio["SVXY"].AveragePrice)) # Debug average price
#closeSVXY = self.Portfolio["SVXY"].AveragePrice
#stopMarketTicketSVXY = self.StopMarketOrder("SVXY",-self.Portfolio['SVXY'].Quantity, closeSVXY * 0.90)
# when fastRSI below 50, sell SVXY & buy VXZ
#if holdingsSVXY <= 0:
if self.fast.Current.Value < 50: # when RSIfast below 50, sell SVXY & buy VXZ
self.Liquidate("SVXY")
self.Debug(str(self.Portfolio["SVXY"].AveragePrice)) # Debug average price
self.SetHoldings("VXZ", 1.0, True)
self.Debug(str(self.Portfolio["VXZ"].AveragePrice)) # Debug average price
#closeVXZ = self.Portfolio["VXZ"].AveragePrice
#stopMarketTicketVXZ = self.StopMarketOrder("VXZ",-self.Portfolio['VXZ'].Quantity, closeVXZ * 0.90)
self.previous = self.Time
def OnEndOfDay(self):
self.Plot("Indicators","fastRSI", self.fast.Current.Value)