Threshold Constraints

PortfolioOptimisers.ThresholdEstimator Type

julia

struct ThresholdEstimator{__T_val, __T_key, __T_dval} <: AbstractConstraintEstimator

Estimator for buy-in threshold portfolio constraints.

ThresholdEstimator specifies a minimum allocation threshold for each asset in a portfolio. Only assets with weights above the threshold are allocated nonzero weight. The estimator supports asset-specific thresholds via dictionaries, pairs, or vectors of pairs, and validates input for non-emptiness.

Fields

val: Asset-specific threshold value(s).
key: Key to specify the asset universe in sets.dict. If nothing, the key is taken from sets.key.
dval: Default value for assets not specified in val.

Constructors

julia

ThresholdEstimator(;
    val::EstValType,
    dval::Option{<:Number} = nothing,
    key::Option{<:AbstractString} = nothing
) -> ThresholdEstimator

Validation

If val is a AbstractDict or AbstractVector, !isempty(val).
If dval is not nothing, it is validated with assert_nonempty_nonneg_finite_val.
If key is not nothing, it is a non-empty string.

View parameters

When port_opt_view is called on this type, the following @vprop-tagged fields are automatically subset to the selected indices:

val: Sliced to the selected indices via port_opt_view.

Examples

julia

julia> ThresholdEstimator(; val = Dict("A" => 0.05, "B" => 0.1))
ThresholdEstimator
   val ┼ Dict{String, Float64}: Dict("B" => 0.1, "A" => 0.05)
   key ┼ nothing
  dval ┴ nothing

julia> ThresholdEstimator(; val = "A" => 0.05)
ThresholdEstimator
   val ┼ Pair{String, Float64}: "A" => 0.05
   key ┼ nothing
  dval ┴ nothing

julia> ThresholdEstimator(; val = 0.05)
ThresholdEstimator
   val ┼ Float64: 0.05
   key ┼ nothing
  dval ┴ nothing

julia> ThresholdEstimator(; val = [0.05])
ThresholdEstimator
   val ┼ Vector{Float64}: [0.05]
   key ┼ nothing
  dval ┴ nothing

julia> ThresholdEstimator(; val = UniformValues())
ThresholdEstimator
   val ┼ UniformValues()
   key ┼ nothing
  dval ┴ nothing

Related

source

PortfolioOptimisers.Threshold Type

julia

struct Threshold{__T_val} <: AbstractConstraintResult

Container for buy-in threshold portfolio constraints.

Threshold stores the minimum allocation threshold(s) for assets in a portfolio. The threshold can be specified as a scalar (applied to all assets) or as a vector of per-asset values. Input validation ensures all thresholds are finite and non-negative.

Fields

val: Threshold value(s) for portfolio weights.

Constructors

julia

Threshold(;
    val::Num_VecNum
) -> Threshold

Validation

val is validated with assert_nonempty_nonneg_finite_val.

View parameters

When port_opt_view is called on this type, the following @vprop-tagged fields are automatically subset to the selected indices:

val: Sliced to the selected indices via port_opt_view.

Examples

julia

julia> Threshold(0.05)
Threshold
  val ┴ Float64: 0.05

julia> Threshold([0.05, 0.1, 0.0])
Threshold
  val ┴ Vector{Float64}: [0.05, 0.1, 0.0]

Related

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PortfolioOptimisers.BtE_Bt Type

julia

const BtE_Bt = Union{<:Threshold, <:ThresholdEstimator}

Alias for a threshold constraint result or estimator.

Matches either a Threshold result or a ThresholdEstimator. Used internally for dispatch in threshold constraint generation.

Related

source

PortfolioOptimisers.VecOptBtE_Bt Type

julia

const VecOptBtE_Bt = AbstractVector{<:Option{<:BtE_Bt}}

Alias for a vector of optional threshold estimators or results.

Represents a collection of optional BtE_Bt elements (threshold estimators or results, or nothing).

Related

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PortfolioOptimisers.BtE_Bt_VecOptBtE_Bt Type

julia

const BtE_Bt_VecOptBtE_Bt = Union{<:BtE_Bt, <:VecOptBtE_Bt}

Alias for a single or vector of optional threshold estimators or results.

Matches either a single BtE_Bt or a vector of optional ones.

Related

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PortfolioOptimisers.VecOptBt Type

julia

const VecOptBt = AbstractVector{<:Option{<:Threshold}}

Alias for a vector of optional threshold results.

Represents a collection of optional Threshold elements.

Related

source

PortfolioOptimisers.Bt_VecOptBt Type

julia

const Bt_VecOptBt = Union{<:Threshold, <:VecOptBt}

Alias for a single threshold result or a vector of optional threshold results.

Matches either a single Threshold or a vector of optional Threshold objects.

Related

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PortfolioOptimisers.threshold_constraints Function

julia

threshold_constraints(t::Option{<:Threshold}, args...; kwargs...)

Propagate or pass through buy-in threshold portfolio constraints.

threshold_constraints returns the input Threshold object or nothing unchanged. This method is used to propagate already constructed buy-in threshold constraints, enabling composability and uniform interface handling in constraint generation workflows.

Arguments

t: An existing Threshold object or nothing.
args...: Additional positional arguments (ignored).
kwargs...: Additional keyword arguments (ignored).

Returns

bt::Option{<:Threshold}: The input constraint object, unchanged.

Examples

julia

julia> threshold_constraints(Threshold(0.05))
Threshold
  val ┴ Float64: 0.05

julia> threshold_constraints(nothing)

Related

source

julia

threshold_constraints(t::ThresholdEstimator, sets::AssetSets;
                      datatype::DataType = Float64, strict::Bool = false)

Generate buy-in threshold portfolio constraints from a ThresholdEstimator and asset set.

threshold_constraints constructs a Threshold object representing minimum allocation thresholds for the assets in sets, using the specifications in t. Supports scalar, vector, dictionary, pair, or custom threshold types for flexible assignment and validation.

Arguments

t: ThresholdEstimator specifying asset-specific threshold values.
sets: AssetSets containing asset names or indices.
datatype: Output data type for thresholds.
strict: If true, enforces strict matching between assets and thresholds (throws error on mismatch); if false, issues a warning.

Returns

bt::Threshold: Object containing threshold values aligned with sets.

Details

Thresholds are extracted and mapped to assets using estimator_to_val.
If a threshold is missing for an asset, assigns zero (no threshold) unless strict is true.

Examples

julia

julia> sets = AssetSets(; dict = Dict("nx" => ["A", "B", "C"]));

julia> t = ThresholdEstimator(Dict("A" => 0.05, "B" => 0.1));

julia> threshold_constraints(t, sets)
Threshold
  val ┴ Vector{Float64}: [0.05, 0.1, 0.0]

Related

source

julia

threshold_constraints(t::VecOptBtE_Bt, sets::AssetSets;
                      kwargs...)

Broadcasts threshold_constraints over the vector.

Provides a uniform interface for processing multiple constraint estimators simultaneously.

source

Threshold Constraints ​

Threshold Constraints