Journal article

Bayesian estimation of generalized hyperbolic skewed Student GARCH models

Published in:
  • Computational Statistics and Data Analysis. - Elsevier. - 2012, vol. 56, no. 11, p. 3035-3054
English Efficient posterior simulators for two GARCH models with generalized hyperbolic disturbances are presented. The first model, GHt-GARCH, is a threshold GARCH with a skewed and heavy-tailed error distribution; in this model, the latent variables that account for skewness and heavy tails are identically and independently distributed. The second model, ODLV-GARCH, is formulated in terms of observation-driven latent variables; it automatically incorporates a risk premium effect. Both models nest the ordinary threshold t-GARCH as a limiting case. The GHt-GARCH and ODLV-GARCH models are compared with each other and with the threshold t-GARCH using five publicly available asset return data sets, by means of Bayes factors, information criteria, and classical forecast evaluation tools. The GHt-GARCH and ODLV-GARCH models both strongly dominate the threshold t-GARCH, and the Bayes factors generally favor GHt-GARCH over ODLV-GARCH. A Markov switching extension of GHt-GARCH is also presented. This extension is found to be an empirical improvement over the single-regime model for one of the five data sets.
Faculté des sciences économiques et sociales
Département d'économie quantitative
  • English
License undefined
Persistent URL

Document views: 10 File downloads:
  • WP_DQE_16.pdf: 4