Overall Statistics |
Total Orders 8 Average Win 0.14% Average Loss -0.37% Compounding Annual Return -4.264% Drawdown 1.100% Expectancy 0.027 Start Equity 100000 End Equity 99302 Net Profit -0.698% Sharpe Ratio -3.071 Sortino Ratio -3.862 Probabilistic Sharpe Ratio 6.137% Loss Rate 25% Win Rate 75% Profit-Loss Ratio 0.37 Alpha -0.039 Beta -0.056 Annual Standard Deviation 0.012 Annual Variance 0 Information Ratio -0.051 Tracking Error 0.144 Treynor Ratio 0.671 Total Fees $6.00 Estimated Strategy Capacity $2200000.00 Lowest Capacity Asset IBM VOBM1Z09FM2U|IBM R735QTJ8XC9X Portfolio Turnover 1.57% |
#region imports from AlgorithmImports import * #endregion class ProtectiveCallAlgorithm(QCAlgorithm): def initialize(self): self.set_start_date(2014, 1, 1) self.set_end_date(2014, 3, 1) self.set_cash(100000) option = self.add_option("IBM") self.symbol = option.symbol option.set_filter(-3, 3, 0, 31) self.call = None # use the underlying equity as the benchmark self.set_benchmark(self.symbol.underlying) def on_data(self, slice): if self.call and self.portfolio[self.call].invested: return chain = slice.option_chains.get(self.symbol) if not chain: return # Find ATM call with the farthest expiry expiry = max([x.expiry for x in chain]) call_contracts = sorted([x for x in chain if x.right == OptionRight.CALL and x.expiry == expiry], key=lambda x: abs(chain.underlying.price - x.strike)) if not call_contracts: return atm_call = call_contracts[0] protective_call = OptionStrategies.protective_call(self.symbol, atm_call.strike, expiry) self.buy(protective_call, 1) self.call = atm_call.symbol