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

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

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.

• Item Type: MPRA Paper
• Language: English
• Keywords: Hidden Markov model, Markov-switching model, state persistence, t-distribution, 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 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes; E - Macroeconomics and Monetary Economics > E4 - Money and Interest Rates > E44 - Financial Markets and the Macroeconomy

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