PortfolioOptimisers.jl

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Base JuMP Optimisation ​

PortfolioOptimisers.BaseJuMPOptimisationEstimator Type
julia
abstract type BaseJuMPOptimisationEstimator <: BaseOptimisationEstimator

Abstract supertype for base JuMP-based portfolio optimisation estimators.

These are configuration-level types (e.g., JuMPOptimiser) that define the optimisation problem setup for JuMP-based optimisers.

Related Types

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PortfolioOptimisers.JuMPOptimisationEstimator Type
julia
abstract type JuMPOptimisationEstimator <: NonFiniteAllocationOptimisationEstimator

Abstract supertype for JuMP-based portfolio optimisation estimators.

JuMP optimisers formulate and solve portfolio optimisation problems using mathematical programming via the JuMP.jl framework.

Related Types

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PortfolioOptimisers.RiskJuMPOptimisationEstimator Type
julia
abstract type RiskJuMPOptimisationEstimator <: JuMPOptimisationEstimator

Abstract supertype for risk-based JuMP portfolio optimisation estimators.

Subtype RiskJuMPOptimisationEstimator to implement optimisers that minimise or constrain risk measures as the primary objective.

Related Types

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PortfolioOptimisers.ObjectiveFunction Type
julia
abstract type ObjectiveFunction <: AbstractEstimator

Abstract supertype for portfolio objective functions.

Subtype ObjectiveFunction to implement portfolio optimisation objectives such as minimum risk, maximum return, or maximum Sharpe ratio.

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PortfolioOptimisers.JuMPReturnsEstimator Type
julia
abstract type JuMPReturnsEstimator <: AbstractEstimator

Abstract supertype for JuMP-based returns estimators used in optimisation models.

JuMPReturnsEstimator types define how expected returns are incorporated into JuMP models.

Related Types

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PortfolioOptimisers.JuMPConstraintEstimator Type
julia
abstract type JuMPConstraintEstimator <: AbstractConstraintEstimator

Abstract supertype for JuMP constraint estimators.

Subtype JuMPConstraintEstimator to implement custom constraints or objectives for JuMP-based portfolio optimisers.

Related Types

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PortfolioOptimisers.CustomJuMPConstraint Type
julia
abstract type CustomJuMPConstraint <: JuMPConstraintEstimator

Abstract supertype for custom JuMP constraint implementations.

Implement add_custom_constraint! to define custom JuMP model constraints.

Related Types

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PortfolioOptimisers.CustomJuMPObjective Type
julia
abstract type CustomJuMPObjective <: JuMPConstraintEstimator

Abstract supertype for custom JuMP objective implementations.

Implement add_custom_objective_term! to add custom terms to the JuMP model objective.

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PortfolioOptimisers.JuMPOptimisationSolution Type
julia
struct JuMPOptimisationSolution{__T_w} <: OptimisationModelResult

Stores the solution (portfolio weights) from a JuMP optimisation model.

Fields

  • w: Optimal portfolio weights (non-empty array of numbers).

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PortfolioOptimisers.add_custom_objective_term! Function
julia
add_custom_objective_term!(args...; kwargs...)

Add a custom objective term to the JuMP model.

No-op fallback. Override this method for subtypes of CustomJuMPObjective to add custom penalty or reward terms to the JuMP model objective.

Arguments

  • args...: JuMP model and custom objective type (ignored in fallback).

  • kwargs...: Additional keyword arguments.

Returns

  • nothing.

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PortfolioOptimisers.add_custom_constraint! Function
julia
add_custom_constraint!(args...; kwargs...)

Add a custom constraint to the JuMP model.

No-op fallback. Override this method for subtypes of CustomJuMPConstraint to add custom constraints to the JuMP model.

Arguments

  • args...: JuMP model and custom constraint type (ignored in fallback).

  • kwargs...: Additional keyword arguments.

Returns

  • nothing.

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PortfolioOptimisers.set_model_scales! Function
julia
set_model_scales!(model::JuMP.Model, so::Number, sc::Number)

Register objective scale so and constraint scale sc as named expressions in the JuMP model.

Arguments

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

  • so::Number: Objective scale factor.

  • sc::Number: Constraint scale factor.

Returns

  • nothing.

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PortfolioOptimisers.set_initial_w! Function
julia
set_initial_w!(args...)
set_initial_w!(w::VecNum, wi::VecNum)

Set initial (warm-start) values for portfolio weight variables in the JuMP model.

The no-op fallback does nothing when wi is not provided. The two-argument method sets JuMP start values for each weight variable.

Arguments

  • w::VecNum: Vector of JuMP weight variables.

  • wi::VecNum: Vector of initial weight values.

Returns

  • nothing.

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PortfolioOptimisers.set_w! Function
julia
set_w!(model::JuMP.Model, X::MatNum, wi::Option{<:VecNum_VecVecNum})

Create portfolio weight variables in the JuMP model and optionally set initial values.

Registers a vector of weight variables w of length size(X, 2) in the model. If wi is provided, sets the initial values via set_initial_w!.

Arguments

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

  • X::MatNum: Asset returns matrix (shape: observations × assets).

  • wi: Optional initial weight values.

Returns

  • nothing.

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PortfolioOptimisers.set_portfolio_returns! Function
julia
set_portfolio_returns!(model::JuMP.Model, X::MatNum)

Compute and register portfolio returns expression X * w in the JuMP model.

If the expression already exists in the model, returns it directly (idempotent).

Arguments

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

  • X::MatNum: Asset returns matrix.

Returns

  • The portfolio returns expression.

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PortfolioOptimisers.set_net_portfolio_returns! Function
julia
set_net_portfolio_returns!(model::JuMP.Model, X::MatNum)

Compute and register net portfolio returns (after fees) in the JuMP model.

Calls set_portfolio_returns! and subtracts fees if present.

Arguments

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

  • X::MatNum: Asset returns matrix.

Returns

  • The net portfolio returns expression.

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PortfolioOptimisers.set_portfolio_returns_plus_one! Function
julia
set_portfolio_returns_plus_one!(model::JuMP.Model, X::MatNum)

Compute and register portfolio gross returns X .+ 1 in the JuMP model.

Used in drawdown and logarithmic return computations.

Arguments

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

  • X::MatNum: Portfolio returns expression.

Returns

  • The gross returns expression X .+ 1.

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PortfolioOptimisers.set_portfolio_drawdowns_plus_one! Function
julia
set_portfolio_drawdowns_plus_one!(model::JuMP.Model, X::MatNum)

Compute and register absolute drawdowns plus one in the JuMP model.

Computes absolute_drawdown_arr(X) .+ 1 and registers it in the model.

Arguments

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

  • X::MatNum: Portfolio returns expression.

Returns

  • The drawdowns-plus-one expression.

Related

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