Bayesian analysis of multivariate stable distributions using\n one-dimensional projections

2015/07/27 by Efthymios G. Tsionas, Tsionas, Mike G.
Computer Science · Economics, Econometrics and Finance · Mathematics · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Financial Risk and Volatility Modeling #Methodology (stat.ME) #Statistical Methods and Inference

paper · pdf · doi:10.48550/arxiv.1507.07323

openalex publication_date 2015/07/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this paper we take up Bayesian inference in general multivariate stable\ndistributions. We exploit the representation of Matsui and Takemura (2009) for\nunivariate projections, and the representation of the distributions in terms of\ntheir spectral measure. We present efficient MCMC schemes to perform the\ncomputations when the spectral measure is approximated discretely or, as we\npropose, by a normal distribution. Appropriate latent variables are introduced\nto implement MCMC. In relation to the discrete approximation, we propose\nefficient computational schemes based on the characteristic function.\n

Citations

• Understanding the Metropolis-Hastings Algorithm

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