Long memory with Markov-Switching GARCH
The paper considers the Markov-Switching GARCH(1,1)-model with time-varying transition probabilities. It derives su?cient conditions for the square of the process to display long memory and provides some additional intuition for the empirical observation that estimated GARCH-parameters often sum to almost one.
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- Prof. Dr. Walter Krämer & Baudouin Tameze Azamo, .
"Structural change and estimated persistence in the GARCH(1,1)-model,"
5, Business and Social Statistics Department, Technische Universität Dortmund, revised May 2006.
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SFB 373 Discussion Papers
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- Christian Francq & Michel Roussignol & Jean-Michel Zakoïan, 1998. "Conditional Heteroskedasticity Driven by Hidden Markov Chains," Working Papers 98-45, Centre de Recherche en Economie et Statistique.
- Markus Haas, 2004. "A New Approach to Markov-Switching GARCH Models," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(4), pages 493-530.
- Hamilton, James D. & Susmel, Raul, 1994.
"Autoregressive conditional heteroskedasticity and changes in regime,"
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- Tom Doan, . "RATS programs to estimate Hamilton-Susmel Markov Switching ARCH model," Statistical Software Components RTZ00083, Boston College Department of Economics.
- Thomas Mikosch & Cătălin Stărică, 2004. "Nonstationarities in Financial Time Series, the Long-Range Dependence, and the IGARCH Effects," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 378-390, February.
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