Hidden Markov models with t components. Increased persistence and other aspects

Jan Bulla

MPRA Paper from University Library of Munich, Germany

Abstract: Hidden Markov models have been applied in many different fields during the last decades, including econometrics and finance. However, the lion’s share of the investigated models is Markovian mixtures of Gaussian distributions. We present an extension to conditional t-distributions, including models with unequal distribution types in different states. It is shown that the extended models, on the one hand, reproduce various stylized facts of daily returns better than the common Gaussian model. On the other hand, robustness to outliers and persistence of the visited states increases significantly.

Keywords: Hidden Markov model; Markov-switching model; state persistence; t-distribution; daily returns (search for similar items in EconPapers)
JEL-codes: C22 C51 C52 E44 (search for similar items in EconPapers)
Date: 2009-10
New Economics Papers: this item is included in nep-ets
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:21830

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