| 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