stochvol

swMATH19383WikidataQ124251214CRANstochvolMaRDI QIDQ31210

Efficient Bayesian Inference for Stochastic Volatility (SV) Models

Gregor Kastner, Darjus Hosszejni

Last update: 26 November 2023

Copyright license: GNU General Public License, version 3.0, GNU General Public License, version 2.0

Software version identifier: 3.2.1, 0.5-0, 0.5-1, 0.6-0, 0.6-1, 0.7-0, 0.7-1, 0.8-0, 0.8-1, 0.8-2, 0.8-4, 0.9-0, 0.9-1, 1.0.0, 1.1.0, 1.1.1, 1.1.2, 1.1.3, 1.2.0, 1.2.1, 1.2.2, 1.2.3, 1.3.0, 1.3.1, 1.3.2, 1.3.3, 2.0.0, 2.0.1, 2.0.2, 2.0.3, 2.0.4, 3.0.0, 3.0.1, 3.0.2, 3.0.3, 3.0.4, 3.0.5, 3.0.6, 3.1.0, 3.2.0, 3.2.3

Source code repository: https://github.com/cran/stochvol

Description

Efficient algorithms for fully Bayesian estimation of stochastic volatility (SV) models with and without asymmetry (leverage) via Markov chain Monte Carlo (MCMC) methods. Methodological details are given in Kastner and Frühwirth-Schnatter (2014) <doi:10.1016/j.csda.2013.01.002> and Hosszejni and Kastner (2019) <doi:10.1007/978-3-030-30611-3_8>; the most common use cases are described in Hosszejni and Kastner (2021) <doi:10.18637/jss.v100.i12> and Kastner (2016) <doi:10.18637/jss.v069.i05> and the package examples.

Cites work

• Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models
• Approaches Toward the Bayesian Estimation of the Stochastic Volatility Model with Leverage
• Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol
• Dealing with Stochastic Volatility in Time Series Using theRPackagestochvol

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