Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/25306
Authors: 
Hautsch, Nikolaus
Ou, Yangguoyi
Year of Publication: 
2008
Series/Report no.: 
SFB 649 discussion paper 2008,063
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.
Subjects: 
Stochastic volatility
Markov chain Monte Carlo
Metropolis-Hastings algorithm Jump Processes
JEL: 
C15
C22
G12
Document Type: 
Working Paper

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