Overall Statistics |
Total Trades 27 Average Win 3.49% Average Loss -3.60% Compounding Annual Return 30.592% Drawdown 10.200% Expectancy 0.363 Net Profit 16.854% Sharpe Ratio 1.313 Loss Rate 31% Win Rate 69% Profit-Loss Ratio 0.97 Alpha 0.246 Beta -3.687 Annual Standard Deviation 0.149 Annual Variance 0.022 Information Ratio 1.22 Tracking Error 0.149 Treynor Ratio -0.053 Total Fees $49.95 |
import numpy as np from QuantConnect.Python import PythonQuandl from QuantConnect.Data.Custom import * import pandas as pd from datetime import timedelta from decimal import Decimal class TermStructureOfVixAlgorithm(QCAlgorithm): def Initialize(self): self.SetStartDate(2018, 1, 1) # Set Start Date self.SetEndDate(2018, 8, 1) # Set End Date self.SetCash(100000) # Set Strategy Cash # Add Quandl VIX price (daily) self.AddData(QuandlVix, "CBOE/VIX", Resolution.Daily, TimeZones.Chicago) # Add VIX futures contract data self.AddFuture(Futures.Indices.VIX).SetFilter(timedelta(0), timedelta(days=182)) # Add E-mini S&P500 futures contract data self.AddFuture(Futures.Indices.SP500EMini).SetFilter(self.UniverseFunc) self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage) self.entryLong = None self.latest_VX = None self.latest_ES = None self.vix = Identity("VIX") self.vx_identity = Identity("VX") self.es_identity = Identity("ES") self.PlotIndicator("VIX", self.vix) self.PlotIndicator("VIX", self.vx_identity) self.PlotIndicator("ES", self.es_identity) def UniverseFunc(self, universe): return universe.FrontMonth() def OnData(self, data): if data.ContainsKey("CBOE/VIX"): self.vix.Update(self.Time, self.Securities["CBOE/VIX"].Price) for chain in data.FutureChains: if chain.Key.Value == "VX": front_VX = sorted(chain.Value, key = lambda x: x.Expiry)[0] self.latest_VX = front_VX.LastPrice if chain.Key.Value == "ES": front_ES = sorted(chain.Value, key = lambda x: x.Expiry)[-1] self.latest_ES = front_ES.LastPrice if not self.Portfolio.Invested and self.entryLong: self.MarketOrder(front_ES.Symbol, 1) self.entryDate = self.Time if self.Portfolio.Invested and self.Time > self.entryDate + timedelta(days=15): self.Liquidate() def OnEndOfDay(self): if self.latest_VX and self.latest_ES: self.vx_identity.Update(self.Time, self.latest_VX) self.es_identity.Update(self.Time, self.latest_ES) self.entryLong = self.vix < self.vx_identity class QuandlVix(PythonQuandl): def __init__(self): self.ValueColumnName = "vix Close"