Backtest

Overall Statistics
Total Trades 6 Average Win 0.63% Average Loss -0.46% Compounding Annual Return -2.404% Drawdown 0.300% Expectancy 0.185 Net Profit -0.224% Sharpe Ratio -1.624 Probabilistic Sharpe Ratio 15.470% Loss Rate 50% Win Rate 50% Profit-Loss Ratio 1.37 Alpha 0.015 Beta -0.063 Annual Standard Deviation 0.006 Annual Variance 0 Information Ratio -6.641 Tracking Error 0.061 Treynor Ratio 0.159 Total Fees $3.00 Estimated Strategy Capacity $600000.00 Lowest Capacity Asset GOOCV WIJN2CDLLEBQ\|GOOCV VP83T1ZUHROL

from AlgorithmImports import *

class LongCallButterflyStrategy(QCAlgorithm): 
    def Initialize(self):
        self.SetStartDate(2017, 2, 1)
        self.SetEndDate(2017, 3, 6)
        self.SetCash(500000)

        option = self.AddOption("GOOG", Resolution.Minute)
        self.symbol = option.Symbol
        option.SetFilter(self.UniverseFunc)

    def UniverseFunc(self, universe):
        return universe.IncludeWeeklys().Strikes(-15, 15).Expiration(timedelta(0), timedelta(31))

    def OnData(self, data):
        # avoid extra orders
        if self.Portfolio.Invested: return

        # Get the OptionChain of the self.symbol
        chain = data.OptionChains.get(self.symbol, None)
        if not chain: return

        # sorted the optionchain by expiration date and choose the furthest date
        expiry = sorted(chain, key = lambda x: x.Expiry, reverse=True)[0].Expiry
        
        # filter the call options from the contracts which expire on the furthest expiration date in the option chain.
        calls = [i for i in chain if i.Expiry == expiry and i.Right == OptionRight.Call]
        if len(calls) == 0: return

        # sort the call options with the same expiration date according to their strike price.
        call_strikes = sorted([x.Strike for x in calls])

        # get at-the-money strike
        atm_strike = sorted(calls, key=lambda x: abs(x.Strike - chain.Underlying.Price))[0].Strike

        # Get the distance between lowest strike price and ATM strike, and highest strike price and ATM strike. 
        # Get the lower value as the spread distance as equidistance is needed for both side.
        spread = min(abs(call_strikes[0] - atm_strike), abs(call_strikes[-1] - atm_strike))

        # select the strike prices for forming the option legs
        itm_strike = atm_strike - spread
        otm_strike = atm_strike + spread

        option_strategy = OptionStrategies.CallButterfly(self.symbol, otm_strike, atm_strike, itm_strike, expiry)
        # We open a position with 1 unit of the option strategy
        self.Buy(option_strategy, 1)
        # self.Sell(option_strategy, 1) if short call butterfly