Bayesian student-t

S.T. Boris Choy; Wai-yin Wan; Chun-man Chan

doi:10.1016/S0731-9053(08)23019-7

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Advances in Econometrics

ISSN: 0731-9053
Series editor(s): Thomas B. Fomby, R. Carter Hill, Ivan Jeliazkov, Juan Carlos Escanciano and Eric Hillebrand

Subject Area: Economics

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Bayesian student-t

Document Information:
Title:	Bayesian student-t
Author(s):	S.T. Boris Choy, Wai-yin Wan, Chun-man Chan
Volume:	23 Editor(s): Siddhartha Chib, William Griffiths, Gary Koop, Dek Terrell ISBN: 978-1-84855-308-8 eISBN: 978-1-84855-309-5
Citation:	S.T. Boris Choy, Wai-yin Wan, Chun-man Chan (2008), Bayesian student-t, in Siddhartha Chib, William Griffiths, Gary Koop, Dek Terrell (ed.) Bayesian Econometrics (Advances in Econometrics, Volume 23), Emerald Group Publishing Limited, pp.595-618
DOI:	10.1016/S0731-9053(08)23019-7 (Permanent URL)
Publisher:	Emerald Group Publishing Limited
Article type:	Chapter Item
Abstract:	The normal error distribution for the observations and log-volatilities in a stochastic volatility (SV) model is replaced by the Student-t distribution for robustness consideration. The model is then called the t-t SV model throughout this paper. The objectives of the paper are twofold. First, we introduce the scale mixtures of uniform (SMU) and the scale mixtures of normal (SMN) representations to the Student-t density and show that the setup of a Gibbs sampler for the t-t SV model can be simplified. For example, the full conditional distribution of the log-volatilities has a truncated normal distribution that enables an efficient Gibbs sampling algorithm. These representations also provide a means for outlier diagnostics. Second, we consider the so-called t SV model with leverage where the observations and log-volatilities follow a bivariate t distribution. Returns on exchange rates of Australian dollar to 10 major currencies are fitted by the t-t SV model and the t SV model with leverage, respectively.