This paper is concerned with simulation-based inference in generalized models of stochastic volatility defined by heavy-tailed Student-t distributions (with unknown degrees of freedom) and exogenous variables in the observation and volatility equations and a jump component in the observation equation. By building on the work of Kim, Shephard and Chib (Rev. Econom. Stud. 65 (1998) 361), we develop efficient Markov chain Monte Carlo algorithms for estimating these models. The paper also discuss...Expand abstract
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- Peer reviewed
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- Elsevier Science B.V.
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- The full-text of this article is not currently available in ORA. Citation: Chib, S., Nardari, F. & Shephard, N. (2002). 'Markov chain Monte Carlo methods for stochastic volatility models', Journal of Econometrics, 108(2), 281-316. [Available at http://www.sciencedirect.com/science/journal/03044076].
Markov chain Monte Carlo methods for stochastic volatility models
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