Overall Statistics
Total Trades
3
Average Win
0%
Average Loss
-0.16%
Compounding Annual Return
88.638%
Drawdown
1.100%
Expectancy
-1
Net Profit
1.342%
Sharpe Ratio
9.132
Probabilistic Sharpe Ratio
94.255%
Loss Rate
100%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
0.427
Beta
-0.217
Annual Standard Deviation
0.068
Annual Variance
0.005
Information Ratio
6.522
Tracking Error
0.23
Treynor Ratio
-2.847
Total Fees
$3.00
Estimated Strategy Capacity
$38000000.00
Lowest Capacity Asset
GOOCV 30AKMEIPIUG06|GOOCV VP83T1ZUHROL
 
#region imports
from AlgorithmImports import *
#endregion

class BasicTemplateOptionsAlgorithm(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2016, 1, 1)
        self.SetEndDate(2016, 1, 10)
        self.SetCash(100000)

        option = self.AddOption("GOOG")
        self.option_symbol = option.Symbol

        # set our strike/expiry filter for this option chain
        option.SetFilter(-2, +2, 0, 180)

        # use the underlying equity as the benchmark
        self.SetBenchmark("GOOG")

    def OnData(self,slice):
        if self.Portfolio.Invested: return

        chain = slice.OptionChains.get(self.option_symbol)
        if chain:
            # we sort the contracts to find at the money (ATM) contract with farthest expiration
            contracts = sorted(sorted(sorted(chain, \
                key = lambda x: abs(chain.Underlying.Price - x.Strike)), \
                key = lambda x: x.Expiry, reverse=True), \
                key = lambda x: x.Right, reverse=True)

            # if found, trade it
            if len(contracts) == 0:
                return
            
            symbol = contracts[0].Symbol
            self.MarketOrder(symbol, 1)
            self.MarketOnCloseOrder(symbol, -1)

    def OnOrderEvent(self, orderEvent):
        self.Log(f'{orderEvent}')