“Exact” and Approximate Methods for Bayesian Inference: Stochastic Volatility Case Study

“Exact” and Approximate Methods for Bayesian Inference: Stochastic Volatility Case Study

We conduct a case study in which we empirically illustrate the performance of different classes of Bayesian inference methods to estimate stochastic volatility models. In particular, we consider how different particle filtering methods affect the variance of the estimated likelihood. We review and c...

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Detalles Bibliográficos
Autor Principal: Yuliya Shapovalova
Formato: Artigo
Idioma:English
Publicado: MDPI AG 2021-04-01
Series:Entropy
Subjects:
Bayesian inference
Markov Chain Monte Carlo
Sequential Monte Carlo
Riemann Manifold Hamiltonian Monte Carlo
integrated nested laplace approximation
fixed-form variational Bayes
Acceso en liña:https://www.mdpi.com/1099-4300/23/4/466

Internet

https://www.mdpi.com/1099-4300/23/4/466

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