Hidden Markov models with t components. Increased persistence and other aspects
AbstractHidden 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.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 21830.
Date of creation: Oct 2009
Date of revision:
Hidden Markov model; Markov-switching model; state persistence; t-distribution; daily returns;
Other versions of this item:
- Jan Bulla, 2010. "Hidden Markov models with t components. Increased persistence and other aspects," Quantitative Finance, Taylor & Francis Journals, Taylor & Francis Journals, vol. 11(3), pages 459-475.
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
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