rmnts_subord: rmnts_subord

In aaron9011/temStaR-v0.814: Tempered Stable Distribution

Description

rmnts_subord generates random vector following the n dimensional NTS distribution using subordination.

r = μ + diag(σ) X,

where

X follows stdNTS_n(α, θ, β, Σ)

Usage

rmnts_subord(strPMNTS, numofsample, rW = NaN, rTau = NaN)

Arguments

strPMNTS

Structure of parameters for the n-dimensional NTS distribution. strPMNTS$ndim : dimension strPMNTS$mu : μ mean vector (column vector) of the input data. strPMNTS$sigma : σ standard deviation vector (column vector) of the input data. strPMNTS$alpha : α of the std NTS distribution (X). strPMNTS$theta : θ of the std NTS distribution (X). strPMNTS$beta : β vector (column vector) of the std NTS distribution (X). strPMNTS$Rho : ρ matrix of the std NTS distribution (X).

numofsample

number of samples.

Value

Simulated NTS random vectors

References

Kim, Y. S. (2020) Portfolio Optimization on the Dispersion Risk and the Asymmetric Tail Risk https://arxiv.org/pdf/2007.13972.pdf

Examples

strPMNTS <- list(ndim = 2,
                 mu = c( 0.00011, 0.00048 ),
                 sigma = c( 0.0162, 0.0231 ),
                 alpha = 1.23,
                 theta = 3.607,
                 beta =  c( -0.1209,  0.0905 ),
                 Rho = matrix( data = c(1.0, 0.55, 0.55, 1.0), nrow = 2, ncol = 2)
)
gensim <- rmnts_subord( strPMNTS, 100 )
plot(gensim)

aaron9011/temStaR-v0.814 documentation built on Dec. 24, 2021, 6:16 p.m.