PerformanceAnalytics.jl

Given the lack of packages that deal with financial analysis in Julia I have decided to translate the functionality of the PerformanceAnalytics package in R to Julia.

Since I took a long break from this and never published it a new package has emerged. This package is registered and implements many but not all the functions available here: PortfolioAnalytics.jl

List of all functions implemented:

Table of Contents

• Asset Price and Return Functions
• Statistical Measures
• Risk Measures
• Performance Measures
• Factor Analysis Functions
• Risk Decomposition
• Utility Functions

Asset Price and Return Functions

• AssetPrice(ticker::String, from::TimeType, to::TimeType, freq::String; exchange_local_time=true)

  • Downloads prices using YFinance.jl

• AssetReturn(x::AssetPrice)

• AssetReturn(ticker::String, from::TimeType, to::TimeType, freq::String)

  • Downloads prices using YFinance.jl and converts them to returns

Return Calculation Functions

• log_diff(x)

• pct_change(x)

• simple_diff(x)

Statistical Measures

Basic Measures

• mean_arith(x)

• mean_geo(returns::Vector{Float64})

• mean_geo_log(returns::Vector{Float64})

• stdvp(x)

• stdvs(x)

• varp(x)

• vars(x)

Advanced Measures

• skew(R, method="simple")

  • Methods: Population, Sample, Fisher

• kurt(R, method="simple")

  • Methods: population, excess, sample, sampleexcess, fisher

• covariance(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}; corrected::Bool=false)

  • Methods:
    • Normal (corrected=false, default)
    • Corrected (corrected=true)

• coskew(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number})

• cokurt(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number})

• hurstindex(R::AbstractArray{<:Number})

Risk Measures

Drawdown Measures

• drawdown(x::AbstractArray{<:Number})

• drawdownpeak(x::AbstractArray{<:Number})

• drawdown_table(x::AbstractArray{<:Number}, dates::AbstractArray{<:TimeType})

• avgdrawdown(x::AbstractArray{<:Number})

• maxdrawdown(x::AbstractArray{<:Number})

Downside Risk Measures

• downsidedeviation(R::AbstractArray{<:Number}, MAR::Number = 0)

• downsidepotential(R::AbstractArray{<:Number}, MAR::Number=0)

• semideviation(R::AbstractArray{<:Number})

• semivariance(R::AbstractArray{<:Number})

Value at Risk and Expected Shortfall

• valueatrisk(R::AbstractArray{<:Number}, p::Number, method::AbstractString="gaussian")

  • Methods: gaussian, historical, cornish_fisher

• expectedshortfall(R::AbstractArray{<:Number}, p::Number, method::AbstractString="gaussian")

  • Methods: gaussian, historical, cornish_fisher

Other Risk Measures

• painindex(R::AbstractArray{<:Number})

Performance Measures

Risk-Adjusted Return Measures

• sharperatio(R::Number, σ::Number, Rf::Number=0.; scale=1)

• sharperatio(R::AbstractArray{<:Number}, Rf::Number=0.; scale)

• adjustedsharpe(R::AbstractArray{<:Number}, Rf::Number=0.; method::AbstractString="population")

• adjustedsharpe(R::Number, σ::Number, S::Number, K::Number, Rf::Number=0.)

• treynorratio(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, Rf::Number=0; modified::Bool=false, scale=1)

• informationratio(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, scale::Number=1)

• appraisalratio(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, Rf::Number=0, method::AbstractString = "appraisal", scale::Number=1)

  • Methods:
    • "appraisal" (default)
    • "modified"
    • "alternative"

Drawdown-based Performance Measures

• calmarratio(R::AbstractArray{<:Number}, scale::Float64=1.)

• burkeratio(R::AbstractArray{<:Number}; Rf::Float64 = 0., modified::Bool = false, scale::Number=1)

• burkeratio(Ra::AbstractArray{<:Number}, Drawdowns::AbstractArray{<:Number}; Rf::Number=0., scale=1)

Relative Performance Measures

• activepremium(Ra::Number, Rb::Number; scalea=1, scaleb=1)

• jensensalpha(Y::AbstractArray{<:Number}, X::AbstractArray{<:Number}...; scale::Number=1)

• trackingerror(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, scale::Number=1)

Other Performance Measures

• bernardoledoitratio(R::AbstractVector{<:Number})

• kappa(R::AbstractArray{<:Number}, MAR::Number=0., k::Number=2)

  • Notable cases:
    • k=1: returns the Sharpe-Omega Ratio
    • k=2: returns the Sortino Ratio

Factor Analysis Functions

• factor_alpha(Y::AbstractArray{<:Number}, X::AbstractArray{<:Number}...)

• factor_loadings(Y::AbstractArray{<:Number}, X::AbstractArray{<:Number}...; intercept::Bool=true)

• factor_regression(Y::AbstractArray{<:Number}, X::AbstractArray{<:Number}...; intercept::Bool=true)

• factor_resid(Y::AbstractArray{<:Number}, X::AbstractArray{<:Number}...; intercept::Bool=true)

Risk Decomposition

• specificrisk(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, Rf::Number=0)

• systematicrisk(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, Rf::Number=0)

• totalrisk(Ra::AbstractArray{<:Number}, Rb::AbstractArray{<:Number}, Rf::Number=0)

Utility Functions

• roll_apply(data::AbstractVector{<:Number}...; fun::Function, window::Int, retain_length::Bool=false, fill_with = NaN, always_return::Bool=false)

• to_annual_return(R::AssetReturn)

• to_monthly_return(R::AssetReturn)

• annualize(R::Number, scale::Float64=252)

A list of all functions and their definitions can be found in the documentation.