Overall Statistics |
Total Trades 12 Average Win 0.02% Average Loss -0.02% Compounding Annual Return -0.241% Drawdown 0.000% Expectancy -0.173 Net Profit -0.026% Sharpe Ratio -5.618 Loss Rate 60% Win Rate 40% Profit-Loss Ratio 1.07 Alpha -0.001 Beta -0.001 Annual Standard Deviation 0 Annual Variance 0 Information Ratio -6.314 Tracking Error 0.143 Treynor Ratio 2.159 Total Fees $2.00 |
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals. # Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. class IronButterflyAlgorithm(QCAlgorithm): def Initialize(self): self.SetStartDate(2017, 4, 1) self.SetEndDate(2017, 5, 10) self.SetCash(10000000) equity = self.AddEquity("GOOG", Resolution.Minute) self.underlyingsymbol = equity.Symbol self.SetBenchmark(equity.Symbol) def OnData(self,slice): if self.Portfolio[self.underlyingsymbol].Quantity != 0: self.Liquidate() if not self.Portfolio.Invested and self.Time.hour != 0 and self.Time.minute != 0: contracts = self.OptionChainProvider.GetOptionContractList(self.underlyingsymbol, self.Time.date()) if len(contracts) == 0 : return filtered_contracts = self.InitialFilter(self.underlyingsymbol, contracts, -10, 10, 0, 30) # sorted the optionchain by expiration date and choose the furthest date expiry = sorted(filtered_contracts, key = lambda x: x.ID.Date)[-1].ID.Date # filter the call and put options from the contracts call = [i for i in filtered_contracts if i.ID.OptionRight == OptionRight.Call and i.ID.Date == expiry] put = [i for i in filtered_contracts if i.ID.OptionRight == OptionRight.Put and i.ID.Date == expiry] # sorted the contracts according to their strike prices call_contracts = sorted(call,key = lambda x: x.ID.StrikePrice) put_contracts = sorted(put,key = lambda x: x.ID.StrikePrice) underlyingPrice = self.Securities["GOOG"].Price atm_put = sorted(put_contracts,key = lambda x: abs(underlyingPrice - x.ID.StrikePrice))[0] atm_call = sorted(call_contracts,key = lambda x: abs(underlyingPrice - x.ID.StrikePrice))[0] otm_call = call_contracts[-1] otm_put = put_contracts[0] self.trade_contracts = [atm_put, atm_call, otm_call, otm_put] for contract in self.trade_contracts: self.AddOptionContract(contract, Resolution.Minute) self.Sell(atm_put ,1) self.Sell(atm_call ,1) self.Buy(otm_call ,1) self.Buy(otm_put ,1) def InitialFilter(self, underlyingsymbol, symbol_list, min_strike_rank, max_strike_rank, min_expiry, max_expiry): ''' This method is an initial filter of option contracts based on the range of strike price and the expiration date ''' if len(symbol_list) == 0 : return # 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 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] filtered_contracts = [i for i in contract_list if i.ID.StrikePrice >= min_strike and i.ID.StrikePrice <= max_strike] return filtered_contracts def OnOrderEvent(self, orderEvent): self.Log(str(orderEvent))