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Markov chain Monte Carlo methods for stochastic volatility models

Chib, Siddhartha; Nardari, Federico; Shephard, Neil G. - In: Journal of econometrics 108 (2002) 2, pp. 281-316

Persistent link: https://www.econbiz.de/10001657610

Analysis of high dimensional multivariate stochastic volatility models

Chib, Siddhartha; Nardari, Federico; Shephard, Neil G. - In: Journal of econometrics 134 (2006) 2, pp. 341-371

Persistent link: https://www.econbiz.de/10003374317

Stochastic volatility : likelihood inference and comparison with ARCH models

Kim, Sangjoon; Shephard, Neil G.; Chib, Siddhartha - 1997

Persistent link: https://www.econbiz.de/10000932608

Stochastic volatility : likelihood inference and comparison with ARCH models

Kim, Sangjoon - In: The review of economic studies 65 (1998) 3, pp. 361-393

Persistent link: https://www.econbiz.de/10001244376

Likelihood inference for discretely observed nonlinear diffusions

Elerian, Ola; Chib, Siddhartha; Shephard, Neil G. - In: Econometrica : journal of the Econometric Society, an … 69 (2001) 4, pp. 959-993

Persistent link: https://www.econbiz.de/10001594726

Stochastic volatility with leverage : fast likelihood inference

Omori, Yasuhiro; Chib, Siddhartha; Shephard, Neil G.; … - 2004

Persistent link: https://www.econbiz.de/10002396452

Likelihood based inference for diffusion driven models

Chib, Siddhartha (contributor); Pitt, Michael K. (contributor) - 2004

Persistent link: https://www.econbiz.de/10002396486

Likelihood based inference for diffusion driven models

Chib, Siddhartha (contributor); Pitt, Michael K. (contributor) - 2004 - [Elektronische Ressource]

Persistent link: https://www.econbiz.de/10002459152

Stochastic volatility with leverage : fast likelihood inference

Omori, Yasuhiro; Chib, Siddhartha; Shephard, Neil G.; … - 2004 - [Elektronische Ressource]

Persistent link: https://www.econbiz.de/10002365024

Stochastic Volatility : Likelihood Inference and Comparison with Arch Models

Kim, Sangjoon; Shephard, Neil G.; Chib, Siddhartha - 1998

In this paper, Markov chain Monte Carlo sampling methods are exploited to provide a unified, practical likelihood-based framework for the analysis of stochastic volatility models. A highly effective method is developed that samples all the unobserved volatilities at once using an approximating...

Persistent link: https://www.econbiz.de/10014075961