stochvol: Efficient Bayesian Inference for Stochastic Volatility (SV) Models

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 Kastner (2016) <doi:10.18637/jss.v069.i05> and the package vignette.

Version: 3.0.4
Depends: R (≥ 3.5)
Imports: Rcpp (≥ 1.0), coda (≥ 0.19), graphics, stats, utils, grDevices
LinkingTo: Rcpp, RcppArmadillo (≥ 0.9.900)
Suggests: mvtnorm, testthat (≥ 2.3.2), knitr, LSD (≥ 4.0-0), RColorBrewer, zoo, factorstochvol (≥ 0.10.1)
Published: 2021-02-09
Author: Darjus Hosszejni ORCID iD [aut, cre], Gregor Kastner ORCID iD [aut]
Maintainer: Darjus Hosszejni <darjus.hosszejni at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: stochvol citation info
Materials: NEWS
In views: Bayesian, Finance, TimeSeries
CRAN checks: stochvol results


Reference manual: stochvol.pdf
Vignettes: Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol
Package source: stochvol_3.0.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: stochvol_3.0.4.tgz, r-oldrel: stochvol_3.0.4.tgz
Old sources: stochvol archive

Reverse dependencies:

Reverse imports: BGVAR, factorstochvol, mfbvar, shrinkTVP
Reverse linking to: BGVAR, factorstochvol, mfbvar, shrinkTVP
Reverse suggests: stochvolTMB, tensorBSS, tsBSS


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