Portfolio Construction

// Create PortfolioTarget objects to form an equal weighted portfolio based on the Insight objects.
SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel());

# Create PortfolioTarget objects to form an equal weighted portfolio based on the Insight objects.
self.set_portfolio_construction(EqualWeightingPortfolioConstructionModel())

// Portfolio construction scaffolding class; basic method arguments.
class MyPortfolioConstructionModel : PortfolioConstructionModel
{
    // Create list of PortfolioTarget objects from Insights.
    public override List<PortfolioTarget> CreateTargets(QCAlgorithm algorithm, Insight[] insights)
    {
        return (List<PortfolioTarget>) base.CreateTargets(algorithm, insights);
    }
    
    // Determine if the portfolio should rebalance based on the provided rebalancing function.
    protected override bool IsRebalanceDue(Insight[] insights, DateTime algorithmUtc) 
    {
        return base.IsRebalanceDue(insights, algorithmUtc);
    }
    
    // Determine the target percent for each insight.
    protected override Dictionary<Insight, double> DetermineTargetPercent(List<Insight> activeInsights)
    {
        return new Dictionary<Insight, double>();
    }

    // Get the target insights to calculate a portfolio target percent. 
    // They will be piped to the DetermineTargetPercent method.
    protected override List<Insight> GetTargetInsights()
    {
        return base.GetTargetInsights();
    }

    // Determine if the portfolio construction model should create a target for this insight.
    protected override bool ShouldCreateTargetForInsight(Insight insight)
    {
        return base.ShouldCreateTargetForInsight(insight);
    }

    // Track universe changes.
    public override void OnSecuritiesChanged(QCAlgorithm algorithm, SecurityChanges changes)
    {
        base.OnSecuritiesChanged(algorithm, changes);
    }
}

 # Portfolio construction scaffolding class; basic method arguments.
class MyPortfolioConstructionModel(PortfolioConstructionModel):
    # Create list of PortfolioTarget objects from Insights.
    def create_targets(self, algorithm: QCAlgorithm, insights: List[Insight]) -> List[PortfolioTarget]:
        return super().create_targets(algorithm, insights)
	
    # Determine if the portfolio should rebalance based on the provided rebalancing function.
    def is_rebalance_due(self, insights: List[Insight], algorithmUtc: datetime) -> bool:
        return super().is_rebalance_due(insights, algorithmUtc)

    # Determine the target percent for each insight.
    def determine_target_percent(self, activeInsights: List[Insight]) -> Dict[Insight, float]:
        return {}

    # Get the target insights to calculate a portfolio target percent. 
    # They will be piped to the determine_target_percent method.
    def get_target_insights(self) -> List[Insight]:
        return super().get_target_insights()

    # Determine if the portfolio construction model should create a target for this insight.
    def should_create_target_for_insight(self, insight: Insight) -> bool:
        return super().should_create_target_for_insight(insight)

    # Track universe changes.
    def on_securities_changed(self, algorithm: QCAlgorithm, changes: SecurityChanges) -> None:
        super().on_securities_changed(algorithm, changes)

// Implement MultipleAlphaPortfolioConstructionModel to handle and utilize insights from multiple Alpha models. 
// The get_target_insights method retrieves current active insights, and determine_target_percent allocates portfolio weights accordingly for integrating and balancing multiple Alpha signals within the portfolio.
public class MultipleAlphaPortfolioConstructionModel : PortfolioConstructionModel
{
    protected override List<Insight> GetTargetInsights()
    {
        return Algorithm.Insights.GetActiveInsights(Algorithm.UtcTime).ToList();
    }

    protected override Dictionary<Insight, double> DetermineTargetPercent(List<Insight> activeInsights)
    {
        return new Dictionary<Insight, double>();
    }
}

# Implement MultipleAlphaPortfolioConstructionModel to handle and utilize insights from multiple Alpha models. 
# The get_target_insights method retrieves current active insights, and determine_target_percent allocates portfolio weights accordingly for integrating and balancing multiple Alpha signals within the portfolio.
class MultipleAlphaPortfolioConstructionModel(PortfolioConstructionModel):
    def get_target_insights(self) -> List[Insight]:
        return self.algorithm.insights.get_active_insights(self.algorithm.utc_time)

    def determine_target_percent(self, activeInsights: List[Insight]) -> Dict[Insight, float]:
        return {}

// Create a new portfolio target for 1200 IBM shares.
var target = new PortfolioTarget("IBM", 1200);

# Create a new portfolio target for 1200 IBM shares.
target = PortfolioTarget("IBM", 1200)

// Calculate target equivalent to 10% of portfolio value
var target = PortfolioTarget.Percent(algorithm, "IBM", 0.1);