PortfolioOptimisers.jl

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Variance Skew Kurtosis Constraints ​

PortfolioOptimisers.set_risk_constraints! Method
julia
set_risk_constraints!(
    model::Model,
    i,
    r::VarianceSkewKurtosis,
    opt::RiskJuMPOptimisationEstimator,
    pr::HighOrderPrior,
    args...;
    prefix,
    kwargs...
) -> Any

Build the joint Variance–Skewness–Kurtosis SDP risk constraints for a VarianceSkewKurtosis risk measure.

Constructs the semidefinite lifting variables W1, W2, W3 and the PSD cone constraint that jointly encodes variance, skewness, and kurtosis. Each sub-risk expression is then bounded and registered separately using set_variance_risk_bounds_and_expression!, with the skewness term using a lower bound (flag = false) because higher skewness is preferred. The composite expression scale_vr * vr - scale_sk * sk + scale_kt * kt is stored and passed to set_risk_bounds_and_expression!.

Arguments

  • model::JuMP.Model: The JuMP optimisation model.

  • i: Constraint index for unique variable and constraint naming.

  • r::VarianceSkewKurtosis: Composite risk measure.

  • opt::RiskJuMPOptimisationEstimator: Risk-based optimisation estimator.

  • pr::HighOrderPrior: High-order prior result providing sigma, sk, kt, D2, L2, S2.

Returns

  • The composite vr_sk_kt_risk JuMP expression.

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