Overall Statistics
Total Orders
3
Average Win
0.56%
Average Loss
0%
Compounding Annual Return
0.636%
Drawdown
0.600%
Expectancy
0
Start Equity
100000
End Equity
100102
Net Profit
0.102%
Sharpe Ratio
-0.194
Sortino Ratio
-0.329
Probabilistic Sharpe Ratio
36.612%
Loss Rate
0%
Win Rate
100%
Profit-Loss Ratio
0
Alpha
-0.006
Beta
-0.093
Annual Standard Deviation
0.015
Annual Variance
0
Information Ratio
0.183
Tracking Error
0.148
Treynor Ratio
0.032
Total Fees
$2.00
Estimated Strategy Capacity
$28000.00
Lowest Capacity Asset
IBM VNWUCLACI1RA|IBM R735QTJ8XC9X
Portfolio Turnover
0.01%
 
#region imports
from AlgorithmImports import *
#endregion

class NakedCallAlgorithm(QCAlgorithm):

    def initialize(self):
        self.set_start_date(2014, 1, 1)
        self.set_end_date(2014, 3, 1)
        self.set_cash(100000)

        option = self.add_option("IBM")
        self.symbol = option.symbol
        option.set_filter(lambda universe: universe.include_weeklys().naked_call(30, 0))

        self.call = None

        # use the underlying equity as the benchmark
        self.set_benchmark(self.symbol.underlying)

    def on_data(self, slice):

        if self.call and self.portfolio[self.call].invested:
            return

        chain = slice.option_chains.get(self.symbol)
        if not chain:
            return

        # Find ATM call with the farthest expiry
        expiry = max([x.expiry for x in chain])
        call_contracts = sorted([x for x in chain
            if x.right == OptionRight.CALL and x.expiry == expiry],
            key=lambda x: abs(chain.underlying.price - x.strike))

        if not call_contracts:
            return

        atm_call = call_contracts[0]

        naked_call = OptionStrategies.naked_call(self.symbol, atm_call.strike, expiry)
        self.buy(naked_call, 1)

        self.call = atm_call.symbol