Overall Statistics |
Total Trades 4 Average Win 0.30% Average Loss -0.33% Compounding Annual Return -72.392% Drawdown 0.400% Expectancy -0.358 Net Profit -0.352% Sharpe Ratio -11.225 Loss Rate 67% Win Rate 33% Profit-Loss Ratio 0.93 Alpha -0.887 Beta -1.405 Annual Standard Deviation 0.04 Annual Variance 0.002 Information Ratio -1.889 Tracking Error 0.068 Treynor Ratio 0.316 Total Fees $2.00 |
class OptionExerciseAssignRegressionAlgorithm(QCAlgorithm): def Initialize(self): self.SetCash(100000) self.SetStartDate(2015,12,24) self.SetEndDate(2015,12,24) option = self.AddOption("GOOG") # set our strike/expiry filter for this option chain option.SetFilter(self.UniverseFunc) self.SetBenchmark("GOOG") self._assignedOption = False def OnData(self, slice): if self.Portfolio.Invested: return for kvp in slice.OptionChains: chain = kvp.Value # find the call options expiring today contracts = filter(lambda x: x.Expiry.date() == self.Time.date() and x.Strike < chain.Underlying.Price and x.Right == OptionRight.Call, chain) # sorted the contracts by their strikes, find the second strike under market price sorted_contracts = sorted(contracts, key = lambda x: x.Strike, reverse = True)[:2] if sorted_contracts: self.MarketOrder(sorted_contracts[0].Symbol, 1) self.MarketOrder(sorted_contracts[1].Symbol, -1) # set our strike/expiry filter for this option chain def UniverseFunc(self, universe): return universe.IncludeWeeklys().Strikes(-2, 2).Expiration(timedelta(0), timedelta(10)) def OnOrderEvent(self, orderEvent): if orderEvent.IsAssignment: order = self.Transactions.GetOrderById(orderEvent.OrderId) if order.Type == OrderType.OptionExercise: self.Log(str(order)) def OnAssignmentOrderEvent(self, assignmentEvent): self.Log(str(assignmentEvent)) self._assignedOption = True