Overall Statistics |
Total Trades 118 Average Win 0.57% Average Loss -0.16% Compounding Annual Return -7.668% Drawdown 70.400% Expectancy 0.342 Net Profit -29.217% Sharpe Ratio -0.106 Loss Rate 71% Win Rate 29% Profit-Loss Ratio 3.59 Alpha 0.598 Beta -32.245 Annual Standard Deviation 0.303 Annual Variance 0.092 Information Ratio -0.171 Tracking Error 0.303 Treynor Ratio 0.001 Total Fees $0.00 |
# https://quantpedia.com/Screener/Details/100 from QuantConnect.Data import SubscriptionDataSource from QuantConnect.Python import PythonData from datetime import date, timedelta, datetime from decimal import Decimal import numpy as np from sklearn import datasets, linear_model class TradeWtiBrentSpreadAlgorithm(QCAlgorithm): def Initialize(self): self.SetStartDate(2014, 1, 1) self.SetEndDate(2018, 5, 1) self.SetCash(1000000) # import the custom data self.AddData(WTI, "WTI", Resolution.Daily) self.AddData(BRENT, "BRENT", Resolution.Daily) # create the moving average indicator of the pread = WTI price - BRENT price self.SpreadSMA = SimpleMovingAverage(20) hist = self.History(["WTI", "BRENT"], 400, Resolution.Daily)["value"].unstack(level=0).dropna() hist_20days = hist[-20:] spread = (hist_20days["WTI"] - hist_20days["BRENT"]).dropna() for index, value in spread.items(): self.SpreadSMA.Update(index, value) # linear regression to decide the fair value hist_one_year = hist[-252:] X = hist_one_year["WTI"][:, np.newaxis] y = hist_one_year["BRENT"] self.regr = linear_model.LinearRegression() self.regr.fit(X, y) # Add the spread plot and mark the long/short spread point spreadPlot = Chart("Spread Plot") spreadPlot.AddSeries(Series("Spread", SeriesType.Line, 0)) spreadPlot.AddSeries(Series("Long Spread Trade", SeriesType.Scatter, 0)) spreadPlot.AddSeries(Series("Short Spread Trade", SeriesType.Scatter, 0)) self.AddChart(spreadPlot) def OnData(self, data): if not (data.ContainsKey("WTI") and data.ContainsKey("BRENT")): return self.Plot("Spread Plot", "Spread", data["WTI"].Price - data["BRENT"].Price) self.SpreadSMA.Update(self.Time, data["WTI"].Price - data["BRENT"].Price) if not self.SpreadSMA.IsReady: return spread = self.Securities["WTI"].Price - self.Securities["BRENT"].Price fair_value =self.Securities["WTI"].Price - Decimal(self.regr.predict(self.Securities["WTI"].Price)[0]) if spread > self.SpreadSMA.Current.Value and not (self.Portfolio["WTI"].IsShort and self.Portfolio["BRENT"].IsLong): self.SetHoldings("WTI", -0.5) self.SetHoldings("BRENT", 0.5) self.Plot("Spread Plot", "Long Spread Trade", data["WTI"].Price - data["BRENT"].Price) elif spread < self.SpreadSMA.Current.Value and not (self.Portfolio["WTI"].IsLong and self.Portfolio["BRENT"].IsShort): self.SetHoldings("WTI", 0.5) self.SetHoldings("BRENT", -0.5) self.Plot("Spread Plot", "Short Spread Trade", data["WTI"].Price - data["BRENT"].Price) if self.Portfolio["WTI"].IsShort and self.Portfolio["BRENT"].IsLong and spread < fair_value: self.Liquidate() if self.Portfolio["WTI"].IsLong and self.Portfolio["BRENT"].IsShort and spread > fair_value: self.Liquidate() class WTI(PythonData): "Class to import WTI Spot Price(Dollars per Barrel) data from Dropbox" def GetSource(self, config, date, isLiveMode): return SubscriptionDataSource("https://www.dropbox.com/s/jpie3z6j0stp97d/wti-crude-oil-prices-10-year-daily.csv?dl=1", SubscriptionTransportMedium.RemoteFile) def Reader(self, config, line, date, isLiveMode): if not (line.strip() and line[1].isdigit()): return None index = WTI() index.Symbol = config.Symbol try: # Example File Format: (Data starts from 08/11/2008) # date value # 8/11/08 114.44 data = line.split(',') index.Time = datetime.strptime(data[0], "%Y-%m-%d") index.Value = Decimal(data[1]) except: return None return index class BRENT(PythonData): "Class to import BRENT Spot Price(Dollars per Barrel) data from Dropbox" def GetSource(self, config, date, isLiveMode): return SubscriptionDataSource("https://www.dropbox.com/s/w380c4n7xjmdqxl/brent-crude-oil-prices-10-year-daily.csv?dl=1", SubscriptionTransportMedium.RemoteFile) def Reader(self, config, line, date, isLiveMode): if not (line.strip() and line[1].isdigit()): return None index = BRENT() index.Symbol = config.Symbol try: # Example File Format: (Data starts from 08/11/2008) # date value # 8/11/08 110.54 data = line.split(',') index.Time = datetime.strptime(data[0], "%Y-%m-%d") index.Value = Decimal(data[1]) except: return None return index