Overall Statistics |
Total Trades 420 Average Win 0.00% Average Loss 0.00% Compounding Annual Return -0.130% Drawdown 0.500% Expectancy -0.398 Net Profit -0.391% Sharpe Ratio -1.09 Probabilistic Sharpe Ratio 0.000% Loss Rate 65% Win Rate 35% Profit-Loss Ratio 0.71 Alpha -0.001 Beta 0 Annual Standard Deviation 0.001 Annual Variance 0 Information Ratio -0.709 Tracking Error 0.118 Treynor Ratio -8.203 Total Fees $420.00 |
class LongStraddleAlgorithm(QCAlgorithm): def Initialize(self): self.SetStartDate(2016, 1, 1) self.SetEndDate(2019, 1, 1) self.SetCash(100000) self.equity = self.AddEquity("SPY", Resolution.Minute) self.equity.SetDataNormalizationMode(DataNormalizationMode.Raw) self.underlyingsymbol = self.equity.Symbol # use the underlying equity GOOG as the benchmark self.SetBenchmark(self.underlyingsymbol) self.Schedule.On(self.DateRules.EveryDay(),self.TimeRules.At(15,30),self.close_pos) self.call_cost = 0 self.put_cost = 0 def OnData(self,slice): if not self.Portfolio.Invested: contracts = self.OptionChainProvider.GetOptionContractList(self.underlyingsymbol, self.Time.date()) if self.Time.hour == 9 and self.Time.minute == 32: self.TradeOptions(contracts) self.call_cost = self.Securities[self.call.Value].Price self.put_cost = self.Securities[self.put.Value].Price if self.Portfolio.Invested: #if price of underlying goes beyond the range of (- 2%) it will liquidate if self.Securities[self.call.Value].Price < 0.98 * self.call_cost: self.Liquidate(self.call.Value) self.Debug("call liquidated") elif self.Securities[self.put.Value].Price < 0.98 * self.put_cost: self.Liquidate(self.put.Value) self.Debug("put liquidated") def TradeOptions(self,contracts): # run CoarseSelection method and get a list of contracts expire within 0 to 8 days from now on # and the strike price between rank -1 to rank 1 filtered_contracts = self.CoarseSelection(self.underlyingsymbol, contracts, -1, 1, 0, 8) if filtered_contracts is None: return expiry = sorted(filtered_contracts,key = lambda x: x.ID.Date, reverse=True)[0].ID.Date # filter the call options from the contracts expire on that date call = [i for i in filtered_contracts if i.ID.Date == expiry and i.ID.OptionRight == 0] # sorted the contracts according to their ATM strike prices call_contracts = sorted(call , key = lambda x: abs(x.ID.StrikePrice-self.Securities[self.underlyingsymbol].Price)) if len(call_contracts) <= 0: return self.call = call_contracts[0] for i in filtered_contracts: if i.ID.Date == expiry and i.ID.OptionRight == 1 and i.ID.StrikePrice ==call_contracts[0].ID.StrikePrice: self.put = i self.AddOptionContract(self.call, Resolution.Minute) self.AddOptionContract(self.put, Resolution.Minute) self.Sell(self.call.Value ,1) self.Sell(self.put.Value ,1) def CoarseSelection(self, underlyingsymbol, symbol_list, min_strike_rank, max_strike_rank, min_expiry, max_expiry): # fitler the contracts based on the expiry range contract_list = [i for i in symbol_list if min_expiry < (i.ID.Date.date() - self.Time.date()).days < max_expiry] # find the strike price of ATM option if len(contract_list) <= 0: return atm_strike = sorted(contract_list, key = lambda x: abs(x.ID.StrikePrice - self.Securities[underlyingsymbol].Price))[0].ID.StrikePrice strike_list = sorted(set([i.ID.StrikePrice for i in contract_list])) # find the index of ATM strike in the sorted strike list atm_strike_rank = strike_list.index(atm_strike) try: min_strike = strike_list[atm_strike_rank + min_strike_rank] max_strike = strike_list[atm_strike_rank + max_strike_rank] except: min_strike = strike_list[0] max_strike = strike_list[-1] # filter the contracts based on the range of the strike price rank filtered_contracts = [i for i in contract_list if i.ID.StrikePrice >= min_strike and i.ID.StrikePrice <= max_strike] return filtered_contracts def close_pos(self): if self.Portfolio.Invested: self.Liquidate()