Overall Statistics |
Total Orders 6 Average Win 0.59% Average Loss -0.43% Compounding Annual Return -2.022% Drawdown 0.300% Expectancy -0.214 Start Equity 500000 End Equity 499058.7 Net Profit -0.188% Sharpe Ratio -3.531 Sortino Ratio -2.888 Probabilistic Sharpe Ratio 16.027% Loss Rate 67% Win Rate 33% Profit-Loss Ratio 1.36 Alpha 0.008 Beta -0.076 Annual Standard Deviation 0.006 Annual Variance 0 Information Ratio -6.548 Tracking Error 0.062 Treynor Ratio 0.282 Total Fees $3.30 Estimated Strategy Capacity $2800000.00 Lowest Capacity Asset GOOCV 30HNN7SCSV7PI|GOOCV VP83T1ZUHROL Portfolio Turnover 0.53% |
from AlgorithmImports import * class PutButterflyStrategy(QCAlgorithm): def initialize(self): self.set_start_date(2017, 2, 1) self.set_end_date(2017, 3, 6) self.set_cash(500000) option = self.add_option("GOOG", Resolution.MINUTE) self.symbol = option.symbol option.set_filter(self.universe_func) def universe_func(self, universe): return universe.include_weeklys().strikes(-15, 15).expiration(timedelta(0), timedelta(31)) def on_data(self, data): # avoid extra orders if self.portfolio.invested: return # Get the OptionChain of the self.symbol chain = data.option_chains.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 put options from the contracts which expire on the furthest expiration date in the option chain. puts = [i for i in chain if i.expiry == expiry and i.right == OptionRight.PUT] if len(puts) == 0: return # sort the put options with the same expiration date according to their strike price. put_strikes = sorted([x.strike for x in puts]) # get at-the-money strike atm_strike = sorted(puts, 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(put_strikes[0] - atm_strike), abs(put_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.put_butterfly(self.symbol, itm_strike, atm_strike, otm_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 put butterfly