Overall Statistics
Total Trades
6
Average Win
0%
Average Loss
-0.37%
Compounding Annual Return
-0.818%
Drawdown
4.000%
Expectancy
-1
Net Profit
-0.132%
Sharpe Ratio
-0.082
Probabilistic Sharpe Ratio
30.295%
Loss Rate
100%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
0.004
Beta
0.385
Annual Standard Deviation
0.053
Annual Variance
0.003
Information Ratio
0.217
Tracking Error
0.084
Treynor Ratio
-0.011
Total Fees
$4.00
Estimated Strategy Capacity
$210000.00
Lowest Capacity Asset
IBM R735QTJ8XC9X
 
#region imports
from AlgorithmImports import *
#endregion
from datetime import timedelta

class CoveredCallAlgorithm(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2014, 1, 1)
        self.SetEndDate(2014, 3, 1)
        self.SetCash(100000)
        equity = self.AddEquity("IBM")
        option = self.AddOption("IBM")
        self.symbol = option.Symbol

        # set strike/expiry filter for this option chain
        option.SetFilter(-3, 3, 0, 30)
        # use the underlying equity as the benchmark
        self.SetBenchmark(equity.Symbol)
 
        
    def OnData(self,slice):
        if not self.Portfolio[self.symbol.Underlying].Invested:
            # buy 100 shares of underlying stocks
            self.MarketOrder(self.symbol.Underlying, 100)

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

        if any([x for x in self.Portfolio.Values
            if x.Invested and x.Type == SecurityType.Option]):
            return

        calls = [x for x in chain if x.Right == OptionRight.Call] 
        if not calls:
            return

        # sorted the contracts according to their expiration dates and choose the ATM options
        calls = sorted(sorted(calls, key=lambda x: abs(chain.Underlying.Price - x.Strike)), 
                                        key = lambda x: x.Expiry, reverse=True)

        # short the call options
        self.MarketOrder(calls[0].Symbol, 1)     
    
    def OnOrderEvent(self, orderEvent):
        self.Log(f'{orderEvent}')