Stochastic Volatility with Leverage: Fast Likelihood Inference

Yasuhiro Omori (), Siddhartha Chib, Neil Shephard () and Jouchi Nakajima
Additional contact information
Siddhartha Chib: Olin School of Business, Washington University

No CIRJE-F-297, CIRJE F-Series from CIRJE, Faculty of Economics, University of Tokyo

Abstract: Kim, Shephard, and Chib (1998) provided a Bayesian analysis of stochastic volatility models based on a fast and reliable Markov chain Monte Carlo (MCMC) algorithm. Their method ruled out the leverage effect, which is known to be important in applications. Despite this, their basic method has been extensively used in the financial economics literature and more recently in macroeconometrics. In this paper we show how the basic approach can be extended in a novel way to stochastic volatility models with leverage without altering the essence of the original approach. Several illustrative examples are provided.

Pages: 24 pages
Date: 2004-08
New Economics Papers: this item is included in nep-cmp, nep-ecm, nep-ets, nep-fin and nep-rmg
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Citations: View citations in EconPapers (4)

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http://www.cirje.e.u-tokyo.ac.jp/research/dp/2004/2004cf297.pdf (application/pdf)

Related works:
Working Paper: Stochastic volatility with leverage: fast likelihood inference (2004)
Working Paper: Stochastic volatility with leverage: fast likelihood inference (2004)
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