Overall Statistics Total Trades 0 Average Win 0% Average Loss 0% Compounding Annual Return 0% Drawdown 0% Expectancy 0 Net Profit 0% Sharpe Ratio 0 Loss Rate 0% 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 \$0.00
```import numpy as np
from datetime import timedelta

### <summary>
### Basic template algorithm simply initializes the date range and cash. This is a skeleton
### framework you can use for designing an algorithm.
### </summary>
class BasicTemplateAlgorithm(QCAlgorithm):
'''Basic template algorithm simply initializes the date range and cash'''

def Initialize(self):
self.SetStartDate(2017, 6, 1)
self.SetEndDate(2017, 6, 15)
self.AddEquity("IBM", Resolution.Minute)
self.option = self.AddOption("IBM", Resolution.Minute)
self.option.SetFilter(-3, +3, timedelta(0), timedelta(30))
self.Schedule.On(self.DateRules.EveryDay("IBM"),self.TimeRules.AfterMarketOpen("IBM", 60),Action(self.print_first_hour))

def OnData(self, slice):
self.option_data = slice

def print_first_hour(self):
for chain in self.option_data.OptionChains.Values:
contracts = sorted(sorted(chain, key = lambda x: abs(chain.Underlying.Price - x.Strike)), key = lambda x: x.Expiry, reverse=True)
price = contracts[0].LastPrice
self.Debug(str(price))```