Overall Statistics Total Trades 8089 Average Win 0.99% Average Loss -0.85% Compounding Annual Return -4.117% Drawdown 70.800% Expectancy 0.039 Net Profit -61.321% Sharpe Ratio -0.188 Probabilistic Sharpe Ratio 0.000% Loss Rate 52% Win Rate 48% Profit-Loss Ratio 1.17 Alpha -0.024 Beta 0.028 Annual Standard Deviation 0.117 Annual Variance 0.014 Information Ratio -0.414 Tracking Error 0.196 Treynor Ratio -0.791 Total Fees $7186.62 Estimated Strategy Capacity$0 Lowest Capacity Asset ICE_WT1.QuantpediaFutures 2S
#region imports
from AlgorithmImports import *
#endregion
#
# A 20-day moving average of WTI/Brent spread is calculated each day. If the current spread value is above SMA 20 then we enter a short position
# in the spread on close (betting that the spread will decrease to the fair value represented by SMA 20). The trade is closed at the close of the
# trading day when the spread crosses below fair value. If the current spread value is below SMA 20 then we enter a long position betting that
# the spread will increase and the trade is closed at the close of the trading day when the spread crosses above fair value.

def Initialize(self):
self.SetStartDate(2000, 1, 1)
self.SetCash(100000)

self.symbols = [
"ICE_WT1",  # WTI Crude Futures, Continuous Contract
"ICE_B1"    # Brent Crude Oil Futures, Continuous Contract
]

for symbol in self.symbols:
data.SetLeverage(5)
data.SetFeeModel(CustomFeeModel())

def OnData(self, data):
symbol1 = self.Symbol(self.symbols)
symbol2 = self.Symbol(self.symbols)

if symbol1 in data.Keys and symbol2 in data.Keys and data[symbol1] and data[symbol2]:
price1 = data[symbol1].Price
price2 = data[symbol2].Price

if price1 != 0 and price2 != 0:

# MA calculation.
if (self.Time.date() - self.Securities[symbol1].GetLastData().Time.date()).days < 5 and (self.Time.date() - self.Securities[symbol2].GetLastData().Time.date()).days < 5:

self.SetHoldings(symbol1, -1)
self.SetHoldings(symbol2, 1)
self.SetHoldings(symbol1, 1)
self.SetHoldings(symbol2, -1)
else:
self.Liquidate()

# Quantpedia data.
# NOTE: IMPORTANT: Data order must be ascending (datewise)
class QuantpediaFutures(PythonData):
def GetSource(self, config, date, isLiveMode):
return SubscriptionDataSource("data.quantpedia.com/backtesting_data/futures/{0}.csv".format(config.Symbol.Value), SubscriptionTransportMedium.RemoteFile, FileFormat.Csv)

def Reader(self, config, line, date, isLiveMode):
data = QuantpediaFutures()
data.Symbol = config.Symbol

if not line.isdigit(): return None
split = line.split(';')

data.Time = datetime.strptime(split, "%d.%m.%Y") + timedelta(days=1)
return OrderFee(CashAmount(fee, "USD"))