Overall Statistics
Total Orders
2
Average Win
0%
Average Loss
0%
Compounding Annual Return
6.010%
Drawdown
0.200%
Expectancy
0
Start Equity
500000
End Equity
502458
Net Profit
0.492%
Sharpe Ratio
4.938
Sortino Ratio
7.34
Probabilistic Sharpe Ratio
98.518%
Loss Rate
0%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
-0.006
Beta
0.098
Annual Standard Deviation
0.008
Annual Variance
0
Information Ratio
-8.051
Tracking Error
0.053
Treynor Ratio
0.408
Total Fees
$2.00
Estimated Strategy Capacity
$1600000.00
Lowest Capacity Asset
GOOCV 30HNN7PDAXNLY|GOOCV VP83T1ZUHROL
Portfolio Turnover
0.03%
 
from AlgorithmImports import *

class BullPutSpreadStrategy(QCAlgorithm): 
    def initialize(self) -> None:
        self.set_start_date(2017, 2, 1)
        self.set_end_date(2017, 3, 5)
        self.set_cash(500000)

        option = self.add_option("GOOG", Resolution.MINUTE)
        self.symbol = option.symbol
        option.set_filter(self.universe_func)

    def universe_func(self, universe: OptionFilterUniverse) -> OptionFilterUniverse:
        return universe.include_weeklys().strikes(-15, 15).expiration(timedelta(0), timedelta(31))

    def on_data(self, slice: Slice) -> None:
        if self.portfolio.invested: return

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

        # Get the furthest expiration 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 strikes 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.bull_put_spread(self.symbol, itm_strike, otm_strike, expiry)
        self.buy(option_strategy, 1)