Overall Statistics |

Total Trades 13 Average Win 0.01% Average Loss -0.01% Compounding Annual Return -0.232% Drawdown 0.000% Expectancy -0.211 Net Profit -0.018% Sharpe Ratio -4.09 Loss Rate 60% Win Rate 40% Profit-Loss Ratio 0.97 Alpha 0 Beta -0.002 Annual Standard Deviation 0 Annual Variance 0 Information Ratio -5.773 Tracking Error 0.156 Treynor Ratio 1.1 Total Fees $3.00 |

# 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. from datetime import timedelta class IronButterflyAlgorithm(QCAlgorithm): def Initialize(self): self.SetStartDate(2017, 4, 1) self.SetEndDate(2017, 4, 30) self.SetCash(10000000) equity = self.AddEquity("GOOG", Resolution.Minute) option = self.AddOption("GOOG", Resolution.Minute) self.symbol = option.Symbol option.SetFilter(-10, 10, timedelta(0), timedelta(30)) # use the underlying equity GOOG as the benchmark self.SetBenchmark(equity.Symbol) def OnData(self,slice): if self.Portfolio["GOOG"].Quantity != 0: self.Liquidate() if not self.Portfolio.Invested and self.Time.hour != 0 and self.Time.minute != 0: for i in slice.OptionChains: if i.Key != self.symbol: continue chain = i.Value contract_list = [x for x in chain] # if there is no optionchain or no contracts in this optionchain, pass the instance if (slice.OptionChains.Count == 0) or (len(contract_list) == 0): return # sorted the optionchain by expiration date and choose the furthest date expiry = sorted(chain,key = lambda x: x.Expiry)[-1].Expiry # filter the call and put options from the contracts call = [i for i in chain if i.Right == 0 and i.Expiry == expiry] put = [i for i in chain if i.Right == 1 and i.Expiry == expiry] # sorted the contracts according to their strike prices call_contracts = sorted(call,key = lambda x: x.Strike) put_contracts = sorted(put,key = lambda x: x.Strike) if len(call_contracts) == 0 or len(put_contracts) == 0 : continue # Sell 1 ATM Put atm_put = sorted(put_contracts,key = lambda x: abs(chain.Underlying.Price - x.Strike))[0] self.Sell(atm_put.Symbol ,1) # Sell 1 ATM Call atm_call = sorted(call_contracts,key = lambda x: abs(chain.Underlying.Price - x.Strike))[0] self.Sell(atm_call.Symbol ,1) # Buy 1 OTM Call otm_call = call_contracts[-1] self.Buy(otm_call.Symbol ,1) # Buy 1 OTM Put otm_put = put_contracts[0] self.Buy(otm_put.Symbol ,1) self.trade_contracts = [atm_put, atm_call, otm_call, otm_put] def OnOrderEvent(self, orderEvent): self.Log(str(orderEvent))