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A dynamic Markov regime-switching GARCH model and its cumulative impulse response function

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  • Kim, Yujin
  • Hwang, Eunju

Abstract

This paper concerns with a generalized regime-switching GARCH model to capture dynamic behavior of volatility in financial market. Four-state Markov chain regime-switching is adopted with white noise, stationary, integrated and explosive states. We consider time-dependent transition probabilities of the Markov chain and derive time-dependent probability of each state under the assumption of conditional normality on the noise of the GARCH model. Multi-step ahead volatility is formulated and cumulative impulse response function, which is a measure of persistence in volatility, is discussed. A Monte-Carlo experiment shows the dynamics of the volatilities and time-dependent probabilities as well as the behaviors of the cumulative impulse response functions.

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  • Kim, Yujin & Hwang, Eunju, 2018. "A dynamic Markov regime-switching GARCH model and its cumulative impulse response function," Statistics & Probability Letters, Elsevier, vol. 139(C), pages 20-30.
    • Handle: RePEc:eee:stapro:v:139:y:2018:i:c:p:20-30
    DOI: 10.1016/j.spl.2018.02.059
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    Cited by:

    1. Kuang-Liang Chang & Charles Ka Yui Leung, 2022. "How did the asset markets change after the Global Financial Crisis?," Chapters, in: Charles K.Y. Leung (ed.), Handbook of Real Estate and Macroeconomics, chapter 12, pages 312-336, Edward Elgar Publishing.

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