Overall Statistics |
Total Orders 9 Average Win 0.23% Average Loss -0.38% Compounding Annual Return -2.267% Drawdown 0.200% Expectancy -0.357 Start Equity 500000 End Equity 498943.4 Net Profit -0.211% Sharpe Ratio -5.688 Sortino Ratio -3.36 Probabilistic Sharpe Ratio 1.636% Loss Rate 60% Win Rate 40% Profit-Loss Ratio 0.61 Alpha -0.028 Beta 0.013 Annual Standard Deviation 0.004 Annual Variance 0 Information Ratio -7.16 Tracking Error 0.057 Treynor Ratio -1.739 Total Fees $6.60 Estimated Strategy Capacity $110000.00 Lowest Capacity Asset GOOCV WIJN1DTXIK4M|GOOCV VP83T1ZUHROL Portfolio Turnover 1.95% |
from AlgorithmImports import * class LongCallButterflyStrategy(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().call_butterfly(30, 5) 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 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.short_butterfly_call(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)