Overall Statistics
Total Trades
2
Average Win
0%
Average Loss
-0.24%
Compounding Annual Return
-72.803%
Drawdown
0.300%
Expectancy
-1
Net Profit
-0.240%
Sharpe Ratio
0
Loss Rate
100%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
0
Beta
0
Annual Standard Deviation
0
Annual Variance
0
Information Ratio
0
Tracking Error
0
Treynor Ratio
0
Total Fees
$0.50
# 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 clr import AddReference
AddReference("System")
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Common")

from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from datetime import timedelta

class BasicTemplateOptionsAlgorithm(QCAlgorithm):
    '''This example demonstrates how to add options for a given underlying equity security.
It also shows how you can prefilter contracts easily based on strikes and expirations.
It also shows how you can inspect the option chain to pick a specific option contract to trade.'''

    def Initialize(self):
        self.SetStartDate(2015, 12, 24)
        self.SetEndDate(2015, 12, 24)
        self.SetCash(100000)

        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(-2, +2, timedelta(0), timedelta(180))
        
        # use the underlying equity as the benchmark
        self.SetBenchmark(equity.Symbol)


    def OnData(self,slice):
        if self.Portfolio.Invested: return
            
        for kvp in slice.OptionChains:
            if kvp.Key != self.symbol: continue
            chain = kvp.Value
            
            # we sort the contracts to find at the money (ATM) contract with farthest expiration
            contracts = sorted(sorted(chain, \
                key = lambda x: abs(chain.Underlying.Price - x.Strike)), \
                key = lambda x: x.Expiry, reverse=True)
            
            # if found, trade it
            if len(contracts) == 0: continue
            symbol = contracts[0].Symbol   
            self.MarketOrder(symbol, 1)
            self.MarketOnCloseOrder(symbol, -1)


    def OnOrderEvent(self, orderEvent):
        self.Log(str(orderEvent))