Overall Statistics |
Total Orders 3 Average Win 0% Average Loss 0% Compounding Annual Return -14.575% Drawdown 1.000% Expectancy 0 Start Equity 100000 End Equity 99112 Net Profit -0.888% Sharpe Ratio -2.92 Sortino Ratio -2.392 Probabilistic Sharpe Ratio 10.520% Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha -0.132 Beta -0.15 Annual Standard Deviation 0.041 Annual Variance 0.002 Information Ratio -0.609 Tracking Error 0.078 Treynor Ratio 0.802 Total Fees $3.00 Estimated Strategy Capacity $8700000.00 Lowest Capacity Asset GOOCV WK9O88F8EXFQ|GOOCV VP83T1ZUHROL Portfolio Turnover 0.29% |
# region imports from AlgorithmImports import * # endregion class BullCallLadderOptionStrategy(QCAlgorithm): def initialize(self): self.set_start_date(2017, 4, 1) self.set_end_date(2017, 4, 23) self.set_cash(100000) option = self.add_option("GOOG", Resolution.MINUTE) self._symbol = option.symbol # set our strike/expiry filter for this option chain option.set_filter(lambda x: x.include_weeklys().call_ladder(30, 5, 0, -5)) def on_data(self, slice): if self.portfolio.invested: return # Get the OptionChain chain = slice.option_chains.get(self._symbol, None) if not chain: return # Select the call Option contracts with the furthest expiry expiry = max([x.expiry for x in chain]) calls = [i for i in chain if i.expiry == expiry and i.right == OptionRight.CALL] if not calls: return # Select the strike prices from the remaining contracts strikes = sorted(set(x.strike for x in calls)) if len(strikes) < 3: return low_strike = strikes[0] middle_strike = strikes[1] high_strike = strikes[2] option_strategy = OptionStrategies.bull_call_ladder(self._symbol, low_strike, middle_strike, high_strike, expiry) self.buy(option_strategy, 1)