Bulla, Jan (2009): Hidden Markov models with t components. Increased persistence and other aspects.

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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 tdistributions, 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.
Item Type:  MPRA Paper 

Original Title:  Hidden Markov models with t components. Increased persistence and other aspects 
Language:  English 
Keywords:  Hidden Markov model, Markovswitching model, state persistence, tdistribution, daily returns 
Subjects:  C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C51  Model Construction and Estimation C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C52  Model Evaluation, Validation, and Selection C  Mathematical and Quantitative Methods > C2  Single Equation Models; Single Variables > C22  TimeSeries Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models E  Macroeconomics and Monetary Economics > E4  Money and Interest Rates > E44  Financial Markets and the Macroeconomy 
Item ID:  21830 
Depositing User:  Jan Bulla 
Date Deposited:  07. Apr 2010 05:45 
Last Modified:  13. Feb 2013 23:39 
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URI:  http://mpra.ub.unimuenchen.de/id/eprint/21830 