Overall Statistics
Total Orders
5
Average Win
0.33%
Average Loss
0%
Compounding Annual Return
-0.211%
Drawdown
2.100%
Expectancy
-0.5
Start Equity
100000
End Equity
99966
Net Profit
-0.034%
Sharpe Ratio
-0.311
Sortino Ratio
-0.566
Probabilistic Sharpe Ratio
31.061%
Loss Rate
50%
Win Rate
50%
Profit-Loss Ratio
0
Alpha
-0.014
Beta
-0.191
Annual Standard Deviation
0.028
Annual Variance
0.001
Information Ratio
0.133
Tracking Error
0.162
Treynor Ratio
0.045
Total Fees
$3.00
Estimated Strategy Capacity
$110000.00
Lowest Capacity Asset
IBM R735QTJ8XC9X
Portfolio Turnover
0.63%
 
#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(-3, 3, 0, 31)

        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