A New Approach to Markov-Switching GARCH Models

Posted: 29 Feb 2008

See all articles by Markus Haas

Markus Haas

University of Kiel - Faculty of Economics and Social Sciences

Stefan Mittnik

University of Kiel - Institute of Statistics & Econometrics; Ludwig Maximilian University of Munich (LMU) - Faculty of Economics; CESifo (Center for Economic Studies and Ifo Institute)

Marc S. Paolella

University of Zurich - Department Finance; Swiss Finance Institute

Date Written: 2004

Abstract

The use of Markov-switching models to capture the volatility dynamics of financial time series has grown considerably during past years, in part because they give rise to a plausible interpretation of nonlinearities. Nevertheless, GARCH-type models remain ubiquitous in order to allow for nonlinearities associated with time-varying volatility. Existing methods of combining the two approaches are unsatisfactory, as they either suffer from severe estimation difficulties or else their dynamic properties are not well understood. In this article we present a new Markov-switching GARCH model that overcomes both of these problems. Dynamic properties are derived and their implications for the volatility process discussed. We argue that the disaggregation of the variance process offered by the new model is more plausible than in the existing variants. The approach is illustrated with several exchange rate return series. The results suggest that a promising volatility model is an independent switching GARCH process with a possibly skewed conditional mixture density.

Keywords: conditional volatility, density forecasting, empirical finance, exchange rates, nonlinear time series, regime switching

Suggested Citation

Haas, Markus and Mittnik, Stefan and Paolella, Marc S., A New Approach to Markov-Switching GARCH Models ( 2004). Journal of Financial Econometrics, Vol. 2, No. 4, pp. 493-530, 2004, Available at SSRN: https://ssrn.com/abstract=821731

Markus Haas (Contact Author)

University of Kiel - Faculty of Economics and Social Sciences ( email )

Kiel
Germany

Stefan Mittnik

University of Kiel - Institute of Statistics & Econometrics ( email )

Olshausenstr. 40
Kiel, Schleswig-Holstein 24118
Germany

Ludwig Maximilian University of Munich (LMU) - Faculty of Economics ( email )

Akademiestr.1/III
Munich, D-80539
Germany

CESifo (Center for Economic Studies and Ifo Institute)

Poschinger Str. 5
Munich, DE-81679
Germany

Marc S. Paolella

University of Zurich - Department Finance

Plattenstr. 14
Zürich, 8032
Switzerland

Swiss Finance Institute

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

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