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Bayesian estimation of a Markov-switching threshold asymmetric GARCH model with Student-t innovations

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  • David Ardia

Abstract

A Bayesian estimation of a regime-switching threshold asymmetric GARCH model is proposed. The specification is based on a Markov-switching model with Student-t innovations and K separate GJR(1,1) processes whose asymmetries are located at free non-positive threshold parameters. The model aims at determining whether or not: (i) structural breaks are present within the volatility dynamics; (ii) asymmetries (leverage effects) are present, and are different between regimes and (iii) the threshold parameters (locations of bad news) are similar between regimes. A novel MCMC scheme is proposed which allows for a fully automatic Bayesian estimation of the model. The presence of two distinct volatility regimes is shown in an empirical application to the Swiss Market Index log-returns. The posterior results indicate no differences with regards to the asymmetries and their thresholds when comparing highly volatile periods with the milder ones. Comparisons with a single-regime specification indicates a better in-sample fit and a better forecasting performance for the Markov-switching model. Copyright The Author(s). Journal compilation Royal Economic Society 2008

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Bibliographic Info

Article provided by Royal Economic Society in its journal Econometrics Journal.

Volume (Year): 12 (2009)
Issue (Month): 1 (03)
Pages: 105-126

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Handle: RePEc:ect:emjrnl:v:12:y:2009:i:1:p:105-126

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Cited by:
  1. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2013. "How does news sentiment impact asset volatility? Evidence from long memory and regime-switching approaches," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 436-456.
  2. Raggi, Davide & Bordignon, Silvano, 2012. "Long memory and nonlinearities in realized volatility: A Markov switching approach," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3730-3742.
  3. Ardia, David & Hoogerheide, Lennart F., 2010. "Efficient Bayesian estimation and combination of GARCH-type models," MPRA Paper 22919, University Library of Munich, Germany.
  4. Marcel Aloy & Gilles de Truchis & Gilles Dufrénot & Benjamin Keddad, 2014. "Shift-Volatility Transmission in East Asian Equity Markets," AMSE Working Papers 1402, Aix-Marseille School of Economics, Marseille, France, revised Mar 2014.
  5. Deschamps, Philippe J., 2009. "Bayesian estimation of an extended local scale stochastic volatility model," DQE Working Papers 15, Department of Quantitative Economics, University of Freiburg/Fribourg Switzerland, revised 12 Nov 2011.

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