Relaxed risk budgeting: private API
PortfolioOptimisers.RelaxedRiskBudgetingAlgorithm — Type
abstract type RelaxedRiskBudgetingAlgorithm <: OptimisationAlgorithmAbstract supertype for relaxed risk budgeting algorithm variants.
Related
BasicRelaxedRiskBudgetingRegularisedRelaxedRiskBudgetingRegularisedPenalisedRelaxedRiskBudgetingRelaxedRiskBudgeting
References
- [140] J.-C. Richard and T. Roncalli. Constrained Risk Budgeting Portfolios: Theory, Algorithms, Applications & Puzzles. arXiv preprint arXiv:1902.05710 (2019).
PortfolioOptimisers.relaxed_risk_budgeting_td_defaults — Function
relaxed_risk_budgeting_td_defaults(
) -> @NamedTuple{rba::AssetRiskBudgeting{Nothing, Nothing, LogRiskBudgeting{Nothing}}}
Return the static defaults of the RelaxedRiskBudgeting fields that may hold a TimeDependent.
Shared by the constructor's test-substitution pass and time_dependent_field_defaults, so the fold-less value of a field is declared once. Fields whose static default is nothing are omitted.
Related
PortfolioOptimisers.set_relaxed_risk_budgeting_alg_constraints! — Function
set_relaxed_risk_budgeting_alg_constraints!(alg, model, w, sigma, chol)Add algorithm-specific second-order cone constraints for Relaxed Risk Budgeting.
Dispatches based on the RRB algorithm variant. Adds second-order cone constraints implementing the basic, regularised, or regularised-penalised RRB formulation.
Arguments
alg: RRB algorithm (BasicRelaxedRiskBudgeting,RegularisedRelaxedRiskBudgeting, orRegularisedPenalisedRelaxedRiskBudgeting).model::JuMP.Model: JuMP optimisation model.w::VecJuMPScalar: Portfolio weight variables.sigma::MatNum: Covariance matrix.chol::Option{<:MatNum}: Optional pre-computed Cholesky factor.
Returns
nothing.
Related
PortfolioOptimisers._set_relaxed_risk_budgeting_constraints! — Method
_set_relaxed_risk_budgeting_constraints!(model, ...)Internal function to set relaxed risk budgeting constraints in the JuMP model.
Configures inequality constraints for the relaxed risk budgeting formulation, allowing small deviations from exact budget targets.
Arguments
model: JuMP model.- Additional relaxed risk budgeting parameters.
Returns
nothing.
Related
PortfolioOptimisers.set_relaxed_risk_budgeting_constraints! — Function
set_relaxed_risk_budgeting_constraints!(model, rrb, pr, wb, args...)Add Relaxed Risk Budgeting (RRB) constraints and weight variables to the JuMP model.
Dispatches based on the risk budgeting algorithm type. Configures weight variables, budget constraints, second-order cone constraints, and weight bounds.
Arguments
model::JuMP.Model: JuMP optimisation model.rrb::RelaxedRiskBudgeting: RRB estimator configuration.pr::AbstractPriorResult: Prior result with asset moments.wb::WeightBounds: Weight bounds configuration.args...: Additional arguments (e.g. returns data for factor risk budgeting).
Returns
- Processed risk budgeting attributes.
Related
References
- [140]
- J.-C. Richard and T. Roncalli. Constrained Risk Budgeting Portfolios: Theory, Algorithms, Applications & Puzzles. Technical Report 1902.05710 (arXiv, 2019).