Overall Statistics
Total Orders
2
Average Win
0%
Average Loss
0%
Compounding Annual Return
0.007%
Drawdown
0.100%
Expectancy
0
Start Equity
500000
End Equity
500003
Net Profit
0.001%
Sharpe Ratio
-4.34
Sortino Ratio
-9.555
Probabilistic Sharpe Ratio
89.927%
Loss Rate
0%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
-0.012
Beta
-0.006
Annual Standard Deviation
0.002
Annual Variance
0
Information Ratio
1.023
Tracking Error
0.22
Treynor Ratio
1.655
Total Fees
$2.00
Estimated Strategy Capacity
$4500000.00
Lowest Capacity Asset
GOOCV WSOXW45FPLYE|GOOCV VP83T1ZUHROL
Portfolio Turnover
0.05%
 
from AlgorithmImports import *

class BearCallSpreadStrategy(QCAlgorithm): 

    def initialize(self):
        self.set_start_date(2018, 2, 1)
        self.set_end_date(2018, 3, 5)
        self.set_cash(500000)

        option = self.add_option("GOOG", Resolution.MINUTE)
        self._symbol = option.symbol
        option.set_filter(
            lambda universe: universe.include_weeklys().call_spread(30, 5)
        )

    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 expiry date of the contracts
        expiry = sorted(chain, key=lambda x: x.expiry, reverse=True)[0].expiry
        
        # Select the call Option contracts with the furthest expiry
        calls = [i for i in chain if i.expiry == expiry and i.right == OptionRight.CALL]
        if len(calls) == 0: 
            return

        # Select the ITM and OTM contracts
        ordered_calls = sorted(calls, key=lambda x: x.strike)
        itm_call = ordered_calls[0]
        otm_call = ordered_calls[-1]

        # Place the order
        option_strategy = OptionStrategies.bear_call_spread(
            self._symbol, itm_call.strike, otm_call.strike, expiry
        )
        self.buy(option_strategy, 1)