QuantConnect

from AlgorithmImports import *

class USEquityOptionsUniverseAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self.set_start_date(2021, 1, 1)
        self.set_end_date(2021, 2, 1)
        self.set_cash(10000000)

        # Asynchronous can use computational resources efficiently
        self.universe_settings.asynchronous = True
        # Subscribe to the underlying for the underlying position
        # Set the data normalization mode to raw for strike price comparability
        self.equity = self.add_equity("GOOG", data_normalization_mode=DataNormalizationMode.RAW).symbol
        # Requesting option data and filter for the hedge candidates
        option = self.add_option(self.equity)
        option.set_filter(self.option_filter)
        self.option_symbol = option.symbol

        # Set scheduled event to buy a hedge option contract at market open to eliminate the intra-day movement
        self.schedule.on(
            self.date_rules.every_day(self.equity),
            self.time_rules.after_market_open(self.equity, 1),
            self.buy_hedge_contract
        )

        # Set a scheduled event to sell the hedge contract before market close, since we want to earn from inter-day movement
        # Leave 2 minutes contingency to fill
        self.schedule.on(
            self.date_rules.every_day(self.equity),
            self.time_rules.before_market_close(self.equity, 2),
            self.sell_hedge_contract
        )

        self.hedge = None
        
    def option_filter(self, universe: OptionFilterUniverse) -> OptionFilterUniverse:
        # Select the contracts with delta very close to -1 and high open interest
        # This can effectively hedge most of the price change of the underlying and ensure the liquidity
        # Make sure the contract is expiring close for its tradbility
        return universe.include_weeklys().puts_only().expiration(2, 7).delta(-1, -0.95).open_interest(10, 1000)

    def buy_hedge_contract(self) -> None:
        chain = self.current_slice.option_chains.get(self.option_symbol)
        if chain:
            # Order the underlying if not hold, the order size should match the option contract
            # Order only if option chain data ready for hedging
            if not self.portfolio[self.equity].invested:
                self.market_order(self.equity, self.securities[self.option_symbol].symbol_properties.contract_multiplier)

            # Get the contract with delta closest to -1 (lowest possible delta)
            contract = sorted(chain, key=lambda x: x.greeks.delta)[0]
            self.hedge = contract.symbol
            # Buy 1 deep ITM put with delta close to -1 to eliminate the intraday movement
            self.market_order(self.hedge, 1)
        
    def sell_hedge_contract(self) -> None:
        # Check if any hedge contract position, if so, liquidate before market close to expose to underlying overnight movement
        if self.hedge:
            self.liquidate(self.hedge)
            self.hedge = None

public class USEquityOptionsUniverseAlgorithm : QCAlgorithm
{
    private Symbol _equity, _optionSymbol, _hedge;
    
    public override void Initialize()
    {
        SetStartDate(2021, 1, 1);
        SetEndDate(2021, 2, 1);
        SetCash(10000000);
        // Asynchronous can use computational resources efficiently
        UniverseSettings.Asynchronous = True;

        // Subscribe to the underlying for the underlying position
        // Set the data normalization mode to raw for strike price comparability
        _equity = AddEquity("GOOG", dataNormalizationMode: DataNormalizationMode.Raw).Symbol;
        // Requesting option data and filter for the hedge candidates
        var option = AddOption(_equity);
        _optionSymbol = option.Symbol;
        option.SetFilter(OptionFilter);

        // Set scheduled event to buy a hedge option contract at market open to eliminate the intra-day movement
        Schedule.On(
            DateRules.EveryDay(_equity),
            TimeRules.AfterMarketOpen(_equity, 1),
            BuyHedgeContract
        );

        // Set a scheduled event to sell the hedge contract before market close, since we want to earn from inter-day movement
        // Leave 2 minutes contingency to fill
        Schedule.On(
            DateRules.EveryDay(_equity),
            TimeRules.BeforeMarketClose(_equity, 2),
            SellHedgeContract
        );
    }

    private OptionFilterUniverse OptionFilter(OptionFilterUniverse universe)
    {
        // Select the contracts with delta very close to -1 and high open interest
        // This can effectively hedge most of the price change of the underlying and ensure the liquidity
        // Make sure the contract is expiring close for its tradbility
        return universe
            .IncludeWeeklys()
            .PutsOnly()
            .Expiration(2, 7)
            .Delta(-1m, -0.95m)
            .OpenInterest(10, 1000);
    }

    private void BuyHedgeContract()
    {
        if (CurrentSlice.OptionChains.TryGetValue(_optionSymbol, out var chain))
        {
            // Order the underlying if not hold, the order size should match the option contract
            // Order only if option chain data ready for hedging
            if (!Portfolio[_equity].Invested)
            {
                MarketOrder(_equity, Securities[_optionSymbol].SymbolProperties.ContractMultiplier);
            }

            // Get the contract with delta closest to -1 (lowest possible delta)
            var contract = chain.MinBy(x => x.Greeks.Delta);
            _hedge = contract.Symbol;
            // Buy 1 deep ITM put with delta close to -1 to eliminate the intraday movement
            MarketOrder(_hedge, 1);
        }
    }

    private void SellHedgeContract()
    {
        // Check if any hedge contract position, if so, liquidate before market close to expose to underlying overnight movement
        if (_hedge != None)
        {
            Liquidate(_hedge);
            _hedge = None;
        }
    }
}

from AlgorithmImports import *

class USEquityOptionsUniverseFrameworkAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self.set_start_date(2023, 1, 1)
        self.set_end_date(2023, 12, 31)
        self.set_cash(100000)
        # Asynchronous can use computational resources efficiently
        self.universe_settings.asynchronous = True

        # Universe selection that select based on liquidity of the option contracts (by open interest)
        self.add_universe_selection(EquityOptionsUniverseSelectionModel())
        # Custom alpha model that use Delta and Gamma to signal insights
        self.add_alpha(OptionDeltaGammaAlphaModel())
        # To maintain long-short size equal, use a PCM that order a single contract
        self.set_portfolio_construction(SingleSharePortfolioConstructionModel())

class EquityOptionsUniverseSelectionModel(OptionUniverseSelectionModel):
    def __init__(self) -> None:
        # Daily update with the select_option_chain_symbols function
        super().__init__(timedelta(1), self.select_option_chain_symbols)

    def select_option_chain_symbols(self, dt: datetime) -> List[Symbol]:
        # Select only NVDA options as our focus, which is a highly traded volatile equity with great upward momentum
        return [Symbol.create("NVDA", SecurityType.OPTION, Market.USA)]

    def filter(self, universe: OptionFilterUniverse) -> OptionFilterUniverse:
        # To ensure the liquidity and tradability, make sure the option is not 0-DTE and have a fair open interest
        # A longer TTM will have lower Gamma thus more stable in the local delta-neutral position
        return universe.include_weeklys().expiration(30, 90).open_interest(50, 1000)

class OptionDeltaGammaAlphaModel(AlphaModel):
    def __init__(self) -> None:
        # A day count variable to control the alpha model only trade once a day
        self._day = -1

    def update(self, algorithm: QCAlgorithm, slice: Slice) -> List[Insight]:
        insights = []

        if self._day != slice.time.day:
            # We open position for each option underlying as separate bet
            for _, chain in slice.option_chains.items():
                # For theta-neutral, select the same expiry for both call and put
                expiry = min(x.expiry for x in chain)
                contracts = [x for x in chain if x.expiry == expiry]

                # Calculate delta and gamma per strike price group for later filtering, ensure both call and put available for option strategy
                delta_gamma_symbols = []
                strikes = set(x.strikes for x in contracts if len([y for y in contracts if y.strike == x.strike]) == 2)
                for strike in strikes:
                    # Get both call and put for their aggregated delta and gamma
                    call = next(filter(lambda x: x.right == OptionRight.CALL and x.strike == strike), contracts)
                    put = next(filter(lambda x: x.right == OptionRight.PUT and x.strike == strike), contracts)
                    delta_gamma_symbols.append((call.greeks.delta + put.greeks.delta, call.greeks.gamma + put.greeks.gamma, call.symbol, put.symbol))
                
                if len(delta_gamma_symbols) == 0:
                    continue

                # We want a delta-neutral position, so it is likely to be ATM (like a long straddle)
                # Less than 2d.p. difference is non-significant, which we can risk for better reward
                # Assuming the market direction is up in most scenario, we try to get the strike providing max overall Gamma
                # Make sure the aggregated gamma to be positive to bet on large uptrend
                # So it will earn more when the price really go up higher and higher, but locally immune for small noise
                filtered = [item for item in delta_gamma_symbols if round(item[0], 2) <= 0.01 and item[1] > 0]
                if len(filtered) == 0:
                    continue
                selected = sorted(filtered, key=lambda x: x[1])[0]

                # Provide trade signal and roll the day count to let the position stay for the whole day
                selected_call = selected[2]
                selected_put = selected[3]
                insights.extend([
                    Insight.price(selected_call, Expiry.END_OF_DAY, InsightDirection.UP),
                    Insight.price(selected_put, Expiry.END_OF_DAY, InsightDirection.UP)
                ])
                self._day = slice.time.day
        
        return insights

class SingleSharePortfolioConstructionModel(PortfolioConstructionModel):
    def create_targets(self, algorithm: QCAlgorithm, insights: List[Insight]) -> List[PortfolioTarget]:
        targets = []
        for insight in insights:
            if algorithm.securities[insight.symbol].is_tradable:
                # Use a whole number target to order the exact number of share for size-matching
                targets.append(PortfolioTarget(insight.symbol, insight.direction))
        return targets

public class USEquityOptionsUniverseFrameworkAlgorithm : QCAlgorithm
{
    public override void Initialize()
    {
        SetStartDate(2024, 1, 1);
        SetEndDate(2024, 3, 31);
        SetCash(100000);
        // Asynchronous can use computational resources efficiently
        UniverseSettings.Asynchronous = True;

        // Universe selection that select based on liquidity of the option contracts (by open interest)
        AddUniverseSelection(new EquityOptionsUniverseSelectionModel());
        // Custom alpha model that use Delta and Gamma to signal insights
        AddAlpha(new OptionDeltaGammaAlphaModel());
        // To maintain long-short size equal, use a PCM that order a single contract
        SetPortfolioConstruction(new SingleSharePortfolioConstructionModel());
    }
}       
    
class EquityOptionsUniverseSelectionModel : OptionUniverseSelectionModel
{
    // Daily update with the SelectOptionChainSymbols function
    public EquityOptionsUniverseSelectionModel()
            : base(TimeSpan.FromDays(1), SelectOptionChainSymbols) {}
    
    private static IEnumerable<Symbol> SelectOptionChainSymbols(DateTime utcTime)
    {
        // Select only NVDA options as our focus, which is a highly traded volatile equity with great upward momentum
        return new[] {QuantConnect.Symbol.Create("NVDA", SecurityType.Option, Market.USA)};
    }

    protected override OptionFilterUniverse Filter(OptionFilterUniverse filter)
    {
        // To ensure the liquidity and tradability, make sure the option is not 0-DTE and have a fair open interest
        // A longer TTM will have lower Gamma thus more stable in the local delta-neutral position
        return filter
            .IncludeWeeklys()
            .Expiration(30, 90)
            .OpenInterest(50, 1000);
    }
}
    
class OptionDeltaGammaAlphaModel : AlphaModel
{
    // A day count variable to control the alpha model only trade once a day
    private int _day = -1;

    public override IEnumerable<Insight> Update(QCAlgorithm algorithm, Slice slice)
    {
        var insights = new List<Insight>();
        
        if (_day != slice.Time.Day)
        {
            // We open position for each option underlying as separate bet
            foreach (var kvp in slice.OptionChains)
            {
                var chain = kvp.Value;

                // For theta-neutral, select the same expiry for both call and put
                var expiry = chain.Min(x => x.Expiry);
                var contracts = chain.Where(x => x.Expiry == expiry).ToList();

                // Calculate delta and gamma per strike price group for later filtering, ensure both call and put available for option strategy
                var deltaGammaSymbols = new List<(decimal, decimal, Symbol, Symbol)>();
                var strikes = contracts.Select(x => x.Strike)
                    .Where(x => contracts.Count(y => y.Strike == x) == 2)
                    .Distinct();
                foreach (var strike in strikes)
                {
                    // Get both call and put for their aggregated delta and gamma
                    var call = contracts.Single(x => x.Right == OptionRight.Call && x.Strike == strike);
                    var put = contracts.Single(x => x.Right == OptionRight.Put && x.Strike == strike);
                    deltaGammaSymbols.Add((call.Greeks.Delta + put.Greeks.Delta, call.Greeks.Gamma + put.Greeks.Gamma, call.Symbol, put.Symbol));
                }

                if (deltaGammaSymbols.Count == 0)
                {
                    continue;
                }

                // We want a delta-neutral position, so it is likely to be ATM (like a long straddle)
                // Less than 2d.p. difference is non-significant, which we can risk for better reward
                // Assuming the market direction is up in most scenario, we try to get the strike providing max overall Gamma
                // Make sure the aggregated gamma to be positive to bet on large uptrend
                // So it will earn more when the price really go up higher and higher, but locally immune for small noise
                var filtered = deltaGammaSymbols.Where(item => Math.Round(item.Item1, 2) <= 0.01m && item.Item2 > 0).ToList();
                if (filtered.Count == 0)
                {
                    continue;
                }
                var selected = filtered.OrderByDescending(item => item.Item2).First();

                // Provide trade signal and roll the day count to let the position stay for the whole day
                var selectedCall = selected.Item3;
                var selectedPut = selected.Item4;
                insights.AddRange(new[] {
                    Insight.Price(selectedCall, Expiry.EndOfDay, InsightDirection.Up),
                    Insight.Price(selectedPut, Expiry.EndOfDay, InsightDirection.Up)
                });
                _day = slice.Time.Day;
            }
        }

        return insights;
    }
}
    
class SingleSharePortfolioConstructionModel : PortfolioConstructionModel
{
    public override IEnumerable<PortfolioTarget> CreateTargets(QCAlgorithm algorithm, Insight[] insights)
    {
        var targets = new List<PortfolioTarget>();
        foreach (var insight in insights)
        {
            if (algorithm.Securities[insight.Symbol].IsTradable)
            {
                // Use a whole number target to order the exact number of share for size-matching
                targets.Add(new PortfolioTarget(insight.Symbol, (int) insight.Direction));
            }
        }
        return targets;
    }
}