| Overall Statistics |
|
Total Trades 150 Average Win 0.27% Average Loss -0.12% Compounding Annual Return -91.601% Drawdown 7.800% Expectancy -0.874 Net Profit -7.821% Sharpe Ratio -7.579 Probabilistic Sharpe Ratio 0% Loss Rate 96% Win Rate 4% Profit-Loss Ratio 2.14 Alpha -3.2 Beta 0.608 Annual Standard Deviation 0.122 Annual Variance 0.015 Information Ratio -49.569 Tracking Error 0.094 Treynor Ratio -1.516 Total Fees $150.00 |
import numpy as np
from System.Drawing import Color
class VerticalTransdimensionalCoreWave(QCAlgorithm):
def Initialize(self):
self.SetTimeZone("America/New_York")
self.SetStartDate(2020,9,24)
self.SetEndDate(2020,10,5)
self.TQQQ = self.AddEquity("TQQQ", Resolution.Minute)
self.SetCash(10000) # Set Strategy Cash
self.SetWarmUp(350)
self.Firststock = "TQQQ"
#Indicators that can be changed
self.FirstHMAPeriod = 25
self.AbsAveragePeriod = 15
self.UpperLimitX = 1.5
self.LowerLimitX = -1.5
self.ShortEMA= 85
self.LongEMA = 90
self.CyclePeriod = 10
#HMA Section******************************************
self.Firsthma = self.HMA(self.Firststock, self.FirstHMAPeriod, Resolution.Minute) #Initializing the Hull Moving Average of the First Stock
#self.Secondhma = self.HMA(self.Firststock, self.SecondHMAPeriod, Resolution.Minute) #Initializing the Hull Moving Average of the First Stock
#HMA Value Rate of Change Percent
self.HMAPercent = IndicatorExtensions.Of(RateOfChangePercent(1), self.Firsthma)
self.HMAPercent.Updated += self.HMASlopeUpdated
self.HMAPercentWindow = RollingWindow[float](10)
self.AbsHMAPercent = SimpleMovingAverage(1)
self.HMAPercent.Updated += self.UpdateAbsHMAPercent
self.AbsAveragePercent = IndicatorExtensions.SMA(self.AbsHMAPercent, self.AbsAveragePeriod)
#Plotting****************************************************************
stockPlot = Chart("Trade Plot")
stockPlot.AddSeries(Series("Price Close", SeriesType.Line, 0))
stockPlot.AddSeries(Series("Price Open", SeriesType.Line, 0))
stockPlot.AddSeries(Series("FirstHMA", SeriesType.Line, 0))
stockPlot.AddSeries(Series("SecondHMA", SeriesType.Line, 0))
stockPlot.AddSeries(Series('Buy', SeriesType.Scatter, '$', Color.Green, ScatterMarkerSymbol.Triangle))
stockPlot.AddSeries(Series('Sell', SeriesType.Scatter, '$', Color.Red, ScatterMarkerSymbol.TriangleDown))
self.AddChart(stockPlot)
def UpdateAbsHMAPercent(self, sender, updated):
if not self.HMAPercent.IsReady:
return
self.AbsHMAPercent.Update(self.Time, abs(updated.Value))
if not self.AbsHMAPercent.IsReady:
return
def HMASlopeUpdated(self, sender, updated):
self.HMAPercentWindow.Add(updated.Value)
def OnData(self, data): #Where actions take place and you enter in the criteria to follow
if self.IsWarmingUp: return #warming up the data, starts running the algorithm before the actual start data
if not (self.HMAPercentWindow.IsReady): return
self.UpperLimit = self.AbsAveragePercent.Current.Value * self.UpperLimitX
self.LowerLimit = self.AbsAveragePercent.Current.Value * self.LowerLimitX
if (not self.Portfolio.Invested):
if self.HMAPercentWindow[0] > self.LowerLimit and self.HMAPercentWindow[1] < self.LowerLimit:
self.SetHoldings(self.Firststock, 1, True)
self.Plot("Trade Plot", "Buy", data[self.Firststock].Value)
StopPrice = self.Securities[self.Firststock].Close
self.StopMarketOrder(self.Firststock, -self.Portfolio[self.Firststock].Quantity, StopPrice)
if (self.Portfolio.Invested):
if self.HMAPercentWindow[0] < self.UpperLimit and self.HMAPercentWindow[1] > self.UpperLimit:
self.Liquidate(self.Firststock)
self.Plot("Trade Plot", "Sell", data[self.Firststock].Value)
#Plotting******************************************************************
self.Plot("Trade Plot", "Price Close", data[self.Firststock].Close)
self.Plot("Trade Plot", "FirstHMA", self.Firsthma.Current.Value)
self.Plot("Percent", "PercentHMA", self.HMAPercent.Current.Value)
self.Plot("Percent", "AbsoluteAverage", self.AbsAveragePercent.Current.Value)
self.Plot("Percent", "Upper", self.UpperLimit)
self.Plot("Percent", "Lower", self.LowerLimit)