PortfolioOptimisers.jl

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High Order Factor Prior ​

PortfolioOptimisers.AbstractHighOrderPriorEstimator_F Type
julia
abstract type AbstractHighOrderPriorEstimator_F <: AbstractHighOrderPriorEstimator

High order prior estimator using factor returns.

AbstractHighOrderPriorEstimator_F is the base type for estimators that compute high order moments (such as coskewness and cokurtosis) requiring both asset and factor returns data. All concrete factor-based high order prior estimators should subtype this type.

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PortfolioOptimisers.AbstractHiLoOrderPriorEstimator_F Type
julia
const AbstractHiLoOrderPriorEstimator_F = Union{<:AbstractLowOrderPriorEstimator_F,
                                                <:AbstractHighOrderPriorEstimator_F}

Alias for a union of low-order and high-order factor prior estimator types.

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PortfolioOptimisers.HighOrderFactorPriorEstimator Type
julia
struct HighOrderFactorPriorEstimator{__T_pe, __T_kte, __T_ske, __T_ex, __T_rsd} <: AbstractHighOrderPriorEstimator_F

Represents the High Order Factor Prior Estimator.

HighOrderFactorPriorEstimator extends a low-order factor prior with coskewness and cokurtosis moments estimated from a factor model. It supports error correction of higher-order moments using residuals from the factor regression.

Fields

  • pe: Low-order factor prior estimator (the base estimator providing mean and covariance).

  • kte: Cokurtosis estimator. If nothing, cokurtosis is not estimated.

  • ske: Coskewness estimator. If nothing, coskewness is not estimated.

  • ex: FLoops executor controlling parallelism for the cokurtosis residuals computation.

  • rsd: If true, corrects the higher-order moments using factor regression residuals.

Constructors

julia
HighOrderFactorPriorEstimator(;
    pe::AbstractLowOrderPriorEstimator_F_AF = FactorPrior(),
    kte::Option{<:CokurtosisEstimator} = Cokurtosis(; alg = Full()),
    ske::Option{<:CoskewnessEstimator} = Coskewness(; alg = Full()),
    ex::FLoops.Transducers.Executor = FLoops.ThreadedEx(),
    rsd::Bool = true
) -> HighOrderFactorPriorEstimator

Keywords correspond to the struct's fields.

Examples

julia
julia> HighOrderFactorPriorEstimator()
HighOrderFactorPriorEstimator
   pe ┼ FactorPrior
      │    pe ┼ EmpiricalPrior
      │       │        ce ┼ PortfolioOptimisersCovariance
      │       │           │   ce ┼ Covariance
      │       │           │      │    me ┼ SimpleExpectedReturns
      │       │           │      │       │   w ┴ nothing
      │       │           │      │    ce ┼ GeneralCovariance
      │       │           │      │       │   ce ┼ StatsBase.SimpleCovariance: StatsBase.SimpleCovariance(true)
      │       │           │      │       │    w ┴ nothing
      │       │           │      │   alg ┴ Full()
      │       │           │   mp ┼ DenoiseDetoneAlgMatrixProcessing
      │       │           │      │     pdm ┼ Posdef
      │       │           │      │         │      alg ┼ UnionAll: NearestCorrelationMatrix.Newton
      │       │           │      │         │   kwargs ┴ @NamedTuple{}: NamedTuple()
      │       │           │      │      dn ┼ nothing
      │       │           │      │      dt ┼ nothing
      │       │           │      │     alg ┼ nothing
      │       │           │      │   order ┴ DenoiseDetoneAlg()
      │       │        me ┼ SimpleExpectedReturns
      │       │           │   w ┴ nothing
      │       │   horizon ┴ nothing
      │    mp ┼ DenoiseDetoneAlgMatrixProcessing
      │       │     pdm ┼ Posdef
      │       │         │      alg ┼ UnionAll: NearestCorrelationMatrix.Newton
      │       │         │   kwargs ┴ @NamedTuple{}: NamedTuple()
      │       │      dn ┼ nothing
      │       │      dt ┼ nothing
      │       │     alg ┼ nothing
      │       │   order ┴ DenoiseDetoneAlg()
      │    re ┼ StepwiseRegression
      │       │   crit ┼ PValue
      │       │        │   t ┴ Float64: 0.05
      │       │    alg ┼ Forward()
      │       │    tgt ┼ LinearModel
      │       │        │   kwargs ┴ @NamedTuple{}: NamedTuple()
      │    ve ┼ SimpleVariance
      │       │          me ┼ SimpleExpectedReturns
      │       │             │   w ┴ nothing
      │       │           w ┼ nothing
      │       │   corrected ┴ Bool: true
      │   rsd ┴ Bool: true
  kte ┼ Cokurtosis
      │    me ┼ SimpleExpectedReturns
      │       │   w ┴ nothing
      │    mp ┼ DenoiseDetoneAlgMatrixProcessing
      │       │     pdm ┼ Posdef
      │       │         │      alg ┼ UnionAll: NearestCorrelationMatrix.Newton
      │       │         │   kwargs ┴ @NamedTuple{}: NamedTuple()
      │       │      dn ┼ nothing
      │       │      dt ┼ nothing
      │       │     alg ┼ nothing
      │       │   order ┴ DenoiseDetoneAlg()
      │   alg ┴ Full()
  ske ┼ Coskewness
      │    me ┼ SimpleExpectedReturns
      │       │   w ┴ nothing
      │    mp ┼ DenoiseDetoneAlgMatrixProcessing
      │       │     pdm ┼ Posdef
      │       │         │      alg ┼ UnionAll: NearestCorrelationMatrix.Newton
      │       │         │   kwargs ┴ @NamedTuple{}: NamedTuple()
      │       │      dn ┼ nothing
      │       │      dt ┼ nothing
      │       │     alg ┼ nothing
      │       │   order ┴ DenoiseDetoneAlg()
      │   alg ┴ Full()
   ex ┼ Transducers.ThreadedEx{@NamedTuple{}}: Transducers.ThreadedEx()
  rsd ┴ Bool: true

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