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Infinite-state Markov-switching for dynamic volatility and correlation models

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  • DUFAYS, Arnaud

    (Université catholique de Louvain, CORE, Belgium)

Abstract

Dynamic volatility and correlation models with fixed parameters are restrictive for time series subject to breaks. GARCH and DCC models with changing parameters are specified using the sticky infinite hidden Markov-chain framework. Estimation by Bayesian inference determines the adequate number of regimes as well as the optimal specification (Markov-switching or change-point). The new estimation algorithm is studied in terms of mixing properties and computational time. Applications highlight the flexibility of the model.

Suggested Citation

  • DUFAYS, Arnaud, 2012. "Infinite-state Markov-switching for dynamic volatility and correlation models," LIDAM Discussion Papers CORE 2012043, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvco:2012043
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    File URL: https://sites.uclouvain.be/core/publications/coredp/coredp2012.html
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    References listed on IDEAS

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    2. Luc Bauwens & Jean-François Carpantier & Arnaud Dufays, 2017. "Autoregressive Moving Average Infinite Hidden Markov-Switching Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 162-182, April.
    3. Sudipto Bhattacharya & Claude d’Aspremont & Sergei Guriev & Debapriya Sen & Yair Tauman, 2014. "Cooperation in R&D: Patenting, Licensing, and Contracting," International Series in Operations Research & Management Science, in: Kalyan Chatterjee & William Samuelson (ed.), Game Theory and Business Applications, edition 2, chapter 0, pages 265-286, Springer.
    4. NESTEROV, Yurii & NEMIROVSKI, Arkadi, 2012. "Finding the stationary states of Markov chains by iterative methods," LIDAM Discussion Papers CORE 2012058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Wang, Cindy Shin-Huei & Bauwens, Luc & Hsiao, Cheng, 2013. "Forecasting a long memory process subject to structural breaks," Journal of Econometrics, Elsevier, vol. 177(2), pages 171-184.
    6. WUNSCH, Guillaume & MOUCHART, Michel & RUSSO, Federica, 2012. "Functions and mechanisms in structural-modelling explanations," LIDAM Discussion Papers CORE 2012056, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Jia Liu & John M. Maheu, 2018. "Improving Markov switching models using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(3), pages 297-318, April.
    8. Billio, Monica & Casarin, Roberto & Osuntuyi, Anthony, 2016. "Efficient Gibbs sampling for Markov switching GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 37-57.
    9. Jin, Xin & Maheu, John M., 2016. "Bayesian semiparametric modeling of realized covariance matrices," Journal of Econometrics, Elsevier, vol. 192(1), pages 19-39.
    10. Jean-François Carpantier, 2014. "Specific Markov-switching behaviour for ARMA parameters," DEM Discussion Paper Series 14-07, Department of Economics at the University of Luxembourg.
    11. Maheu, John M. & Yang, Qiao, 2016. "An infinite hidden Markov model for short-term interest rates," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 202-220.
    12. Shuping Shi & Yong Song, 2015. "Identifying Speculative Bubbles Using an Infinite Hidden Markov Model," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 14(1), pages 159-184.
    13. Jin, Xin & Maheu, John M., 2016. "Modeling covariance breakdowns in multivariate GARCH," Journal of Econometrics, Elsevier, vol. 194(1), pages 1-23.
    14. Dufays, A. & Rombouts, V., 2015. "Sparse Change-Point Time Series Models," LIDAM Discussion Papers CORE 2015032, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. ROELS, Guillaume & CHEVALIER, Philippe & WEI, Ying, 2012. "United we stand? Coordinating capacity investment and allocation in joint ventures," LIDAM Discussion Papers CORE 2012045, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

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    More about this item

    Keywords

    Bayesian inference; Markov-switching; GARCH; DCC; infinite hidden Markov model; Dirichlet process;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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