| Overall Statistics |
|
Total Trades 4 Average Win 0% Average Loss -0.24% Compounding Annual Return 1.614% Drawdown 0.800% Expectancy -1 Net Profit 0.399% Sharpe Ratio 0.975 Loss Rate 100% Win Rate 0% Profit-Loss Ratio 0 Alpha -0.012 Beta 0.084 Annual Standard Deviation 0.015 Annual Variance 0 Information Ratio -1.858 Tracking Error 0.163 Treynor Ratio 0.18 Total Fees $0.50 |
from datetime import timedelta
class BullCallSpreadAlgorithm(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2017, 4, 1)
self.SetEndDate(2017, 6, 30)
self.SetCash(1000000)
equity = self.AddEquity("GOOG", Resolution.Minute)
option = self.AddOption("GOOG", Resolution.Minute)
self.symbol = option.Symbol
# set our strike/expiry filter for this option chain
option.SetFilter(-6, 6, timedelta(30), timedelta(60))
# use the underlying equity GOOG as the benchmark
self.SetBenchmark(equity.Symbol)
def OnData(self,slice):
for i in slice.OptionChains:
chains = i.Value
if not self.Portfolio.Invested:
self.TradeOptions(chains)
def TradeOptions(self,chains):
# sorted the optionchain by expiration date and choose the furthest date
expiry = sorted(chains,key = lambda x: x.Expiry, reverse=True)[0].Expiry
# filter the call and put contract
call = [i for i in chains if i.Expiry == expiry and i.Right == OptionRight.Call]
put = [i for i in chains if i.Expiry == expiry and i.Right == OptionRight.Put]
# sorted the contracts according to their strike prices
call_contracts = sorted(call,key = lambda x: x.Strike)
if len(call_contracts) == 0: return
self.call = call_contracts[0]
for i in put:
if i.Strike == self.call.Strike:
self.put = i
self.Buy(self.call.Symbol, 1)
self.Buy(self.put.Symbol ,1)
def OnOrderEvent(self, orderEvent):
self.Log(str(orderEvent))