| 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))