Overall Statistics
Total Trades
2
Average Win
0%
Average Loss
0%
Compounding Annual Return
-6.961%
Drawdown
0.700%
Expectancy
0
Net Profit
-0.604%
Sharpe Ratio
-6.134
Probabilistic Sharpe Ratio
0.144%
Loss Rate
0%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
-0.003
Beta
-0.099
Annual Standard Deviation
0.008
Annual Variance
0
Information Ratio
-8.215
Tracking Error
0.064
Treynor Ratio
0.507
Total Fees
$2.00
Estimated Strategy Capacity
$9100000.00
Lowest Capacity Asset
GOOCV 30HNN7PDAXNLY|GOOCV VP83T1ZUHROL
from AlgorithmImports import *

class BearPutSpreadStrategy(QCAlgorithm): 
    def Initialize(self):
        self.SetStartDate(2017, 2, 1)
        self.SetEndDate(2017, 3, 5)
        self.SetCash(500000)

        option = self.AddOption("GOOG", Resolution.Minute)
        self.symbol = option.Symbol
        option.SetFilter(self.UniverseFunc)

    def UniverseFunc(self, universe):
        return universe.IncludeWeeklys().Strikes(-15, 15).Expiration(timedelta(0), timedelta(31))

    def OnData(self, slice):
        if self.Portfolio.Invested: return

        # Get the OptionChain
        chain = slice.OptionChains.get(self.symbol, None)
        if not chain: return

        # Get the furthest expiry date of the contracts
        expiry = sorted(chain, key = lambda x: x.Expiry, reverse=True)[0].Expiry
        
        # Select the put Option contracts with the furthest expiry
        puts = [i for i in chain if i.Expiry == expiry and i.Right == OptionRight.Put]
        if len(puts) == 0: return

        # Select the ITM and OTM contract strike prices from the remaining contracts
        put_strikes = sorted([x.Strike for x in puts])
        otm_strike = put_strikes[0]
        itm_strike = put_strikes[-1]
        
        option_strategy = OptionStrategies.BearPutSpread(self.symbol, itm_strike, otm_strike, expiry)
        self.Buy(option_strategy, 1)