Dear all
I’m announcing the availability of QuadraticFormsMGHyp.jl. The purpose of the package is to compute tail probabilities and partial moments of
where X\sim \mathrm{MGHyp}(\boldsymbol{\mu},\mathbf{C},\boldsymbol{\gamma},\lambda,\chi,\psi); i.e., X has a d-variate generalized hyperbolic distribution with stochastic representation
where Z has a d-variate standard Normal distribution, \boldsymbol{\mu} and \boldsymbol{\gamma} are constant d-vectors, \mathbf{C} is a d\times d matrix, and Y has a univariate generalized inverse Gaussian distribution with density
The generalized hyperbolic distribution contains as special cases, among others, the Variance-Gamma (\lambda>0), Student’s t (\lambda=-\nu/2, \chi=\nu, \psi=0), Normal Inverse Gaussian (\lambda=-1/2), and Hyperbolic (\lambda=1) distributions.
The package provides exact calculations and saddlepoint approximations. The algorithms are from our paper and generalize those of Imhof (Biometrika, 1961) and Broda (Mathematical Finance, 2012).
Cheers
Simon