Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/25306 
Erscheinungsjahr: 
2008
Schriftenreihe/Nr.: 
SFB 649 Discussion Paper No. 2008,063
Verlag: 
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk, Berlin
Zusammenfassung: 
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.
Schlagwörter: 
Stochastic volatility
Markov chain Monte Carlo
Metropolis-Hastings algorithm Jump Processes
JEL: 
C15
C22
G12
Dokumentart: 
Working Paper

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