Markov-switching GARCH models in finance: a unifying framework with an application to the German stock market
Gerrit Reher and
Bernd Wilfling ()
No 1711, CQE Working Papers from Center for Quantitative Economics (CQE), University of Muenster
In this paper we develop a unifying Markov-switching GARCH model which enables us (1) to specify complex GARCH equations in two distinct Markov-regimes, and (2) to model GARCH equations of different functional forms across the two Markov-regimes. To give a simple example, our flexible Markov-switching approach is capable of estimating an exponential GARCH (EGARCH) specification in the first and a standard GARCH specification in the second Markov-regime. We derive a maximum likelihood estimation framework and apply our general Markov-switching GARCH model to daily excess returns of the German stock market index DAX. Our empirical study has two major findings. First, our estimation results unambiguously indicate that our general model outperforms all conventional Markov-switching GARCH models hitherto estimated in the financial literature. Second, we find significant Markov-switching in the German stock market with substantially differing volatility structures across the regimes.
Keywords: Markov-switching models; GARCH models; Dynamics of stock index returns (search for similar items in EconPapers)
JEL-codes: C5 G10 G15 (search for similar items in EconPapers)
Pages: 29 pages
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:cqe:wpaper:1711
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