Overall Statistics
Total Trades
1
Average Win
0%
Average Loss
0%
Compounding Annual Return
0%
Drawdown
0%
Expectancy
0
Net Profit
0%
Sharpe Ratio
0
Probabilistic Sharpe Ratio
0%
Loss Rate
0%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
0
Beta
0
Annual Standard Deviation
0
Annual Variance
0
Information Ratio
0
Tracking Error
0
Treynor Ratio
0
Total Fees
$2.75
Estimated Strategy Capacity
$420000.00
Lowest Capacity Asset
AAPL XYME7AV9W0O6|AAPL R735QTJ8XC9X
from AlgorithmImports import *
# endregion

class EnergeticYellowGreenFalcon(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2022, 5, 19)  # Set Start Date
        self.SetEndDate(2022, 5, 21)  
        self.SetCash(100000)  # Set Strategy Cash
        self.symbol = self.AddEquity("AAPL", Resolution.Minute).Symbol
        option = self.AddOption("AAPL")
        self.option_symbol = option.Symbol
        self.SetWarmUp(timedelta(days = 30))
        self.order = True
        self.SetSecurityInitializer(self.SecurityInitializer)

    def SecurityInitializer(self, security):
        security.SetMarketPrice(self.GetLastKnownPrice(security))
        security.SetDataNormalizationMode(DataNormalizationMode.Raw)
       

    def OnData(self, data):
        if self.IsWarmingUp:
            return

        
        
        
        if not self.Portfolio.Invested and self.order:
            contract_symbols = self.OptionChainProvider.GetOptionContractList(self.option_symbol, self.Time)
            expiry = min([symbol.ID.Date for symbol in contract_symbols], default="EMPTY")
            filtered_symbols = [symbol for symbol in contract_symbols if symbol.ID.Date == expiry and self.option_symbol.ID.OptionRight == OptionRight.Call]
            self.contract_symbol = sorted(filtered_symbols, key=lambda symbol: symbol.ID.StrikePrice)[0]
            value = self.AddOptionContract(self.contract_symbol)
            shares_to_buy = int(self.Portfolio.Cash / (100*value.AskPrice))
            self.MarketOrder(self.contract_symbol, shares_to_buy)

            self.order = False