PortfolioOptimisers.jl

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Median expected returns ​

PortfolioOptimisers.MedianExpectedReturns Type
julia
struct MedianExpectedReturns{__T_w} <: AbstractExpectedReturnsEstimator

Expected returns estimator that returns the optionally weighted asset medians.

Fields

  • w: Optional observation weights vector observations × 1, or a concrete subtype of DynamicAbstractWeights. If nothing, the computation is unweighted.

Constructors

julia
MedianExpectedReturns(;
    w::Option{<:ObsWeights} = nothing
) -> MedianExpectedReturns

Keywords correspond to the struct's fields.

Examples

julia
julia> me = MedianExpectedReturns()
MedianExpectedReturns
  w ┴ nothing

julia> factory(me, StatsBase.Weights([0.1, 0.2, 0.7]))
MedianExpectedReturns
  w ┴ StatsBase.Weights{Float64, Float64, Vector{Float64}}: [0.1, 0.2, 0.7]

Related

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PortfolioOptimisers.factory Method
julia
factory(ce::MedianExpectedReturns, w::ObsWeights) -> MedianExpectedReturns

Return a new MedianExpectedReturns estimator with observation weights w.

Arguments

  • ce: Median expected returns estimator.

  • w: Observation weights vector observations × 1.

Returns

  • me::MedianExpectedReturns: Updated estimator with weights applied.

Related

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Statistics.mean Method
julia
Statistics.mean(me::MedianExpectedReturns, X::MatNum;
                dims::Int = 1, kwargs...)

Compute expected returns as the median of each asset.

This method returns the median of each asset across observations in X. If me.w is nothing, the median is computed directly with Statistics.median(X; dims = dims). Otherwise, the method computes a weighted median for each asset using the observation weights w.

Arguments

  • me: Median expected returns estimator.

  • X: Data matrix of asset returns (observations × assets).

  • dims: Dimension along which to perform the computation.

  • kwargs: Additional keyword arguments (ignored).

Returns

  • mu::Matrix{<:Number}: Median vector, shaped as (1, N) if dims == 1 or (N, 1) if dims == 2.

Related

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