Overall Statistics
Total Trades
9
Average Win
1.97%
Average Loss
-1.50%
Compounding Annual Return
-6.283%
Drawdown
1.100%
Expectancy
-0.074
Net Profit
-1.058%
Sharpe Ratio
-4.141
Loss Rate
60%
Win Rate
40%
Profit-Loss Ratio
1.32
Alpha
-0.048
Beta
-0.016
Annual Standard Deviation
0.015
Annual Variance
0
Information Ratio
-6.663
Tracking Error
0.144
Treynor Ratio
3.896
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.
from datetime import timedelta

class ButterflySpreadAlgorithm(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2017, 4, 1)
        self.SetEndDate(2017, 5, 30)
        self.SetCash(150000)
        equity = self.AddEquity("GOOG", Resolution.Minute)
        option = self.AddOption("GOOG", Resolution.Minute)
        self.symbol = option.Symbol
        # set our strike/expiry filter for this option chain
        option.SetFilter(-9, 9, timedelta(30), timedelta(60))
        # use the underlying equity GOOG as the benchmark
        self.SetBenchmark(equity.Symbol)
        
    def OnData(self,slice):

             # if there is no securities in portfolio, trade the options 
            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
                    # sorted the optionchain by expiration date and choose the furthest date
                    expiry = sorted(chain,key = lambda x: x.Expiry, reverse=True)[0].Expiry
                    # filter the call options from the contracts expires on that date
                    call = [i for i in chain if i.Expiry == expiry and i.Right == 0]
                    # sorted the contracts according to their strike prices 
                    call_contracts = sorted(call,key = lambda x: x.Strike)    
                    if len(call_contracts) == 0: continue
                    # choose OTM call 
                    self.otm_call = call_contracts[-1]
                    # choose ITM call 
                    self.itm_call = call_contracts[0]
                    # choose ATM call
                    self.atm_call = sorted(call_contracts,key = lambda x: abs(chain.Underlying.Price - x.Strike))[0]
        
                    self.Sell(self.atm_call.Symbol ,2)
                    self.Buy(self.itm_call.Symbol ,1)
                    self.Buy(self.otm_call.Symbol ,1)
            
    def OnOrderEvent(self, orderEvent):
        self.Log(str(orderEvent))