Discrete-time stochastic volatility models and MCMC-based statistical inference

Nikolaus Hautsch and Yangguoyi Ou

No 2008-063, SFB 649 Discussion Papers from Humboldt University Berlin, Collaborative Research Center 649: Economic Risk

Abstract: In this paper, we review the most common specifications of discrete-time stochastic volatility (SV) models and illustrate the major principles of corresponding Markov Chain Monte Carlo (MCMC) based statistical inference. We provide a hands-on ap proach which is easily implemented in empirical applications and financial practice and can be straightforwardly extended in various directions. We illustrate empirical results based on different SV specifications using returns on stock indices and foreign exchange rates.

Keywords: Stochastic volatility; Markov chain Monte Carlo; Metropolis-Hastings algorithm Jump Processes (search for similar items in EconPapers)
JEL-codes: C15 C22 G12 (search for similar items in EconPapers)
Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:sfb649:sfb649dp2008-063

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