Package: stochvol 3.2.5
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 Hosszejni and Kastner (2021) <doi:10.18637/jss.v100.i12> and Kastner (2016) <doi:10.18637/jss.v069.i05> and the package examples.
Authors:
stochvol_3.2.5.tar.gz
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stochvol.pdf |stochvol.html✨
stochvol/json (API)
NEWS
# Install 'stochvol' in R: |
install.packages('stochvol', repos = 'https://cloud.r-project.org') |
Bug tracker:https://github.com/gregorkastner/stochvol/issues0 issues
Pkgdown site:https://gregorkastner.github.io
- exrates - Euro exchange rate data
Conda:r-stochvol-3.2.5(2025-03-25)
Last updated 5 months agofrom:a1b22dc123. Checks:3 OK. Indexed: no.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Mar 28 2025 |
R-4.5-linux-x86_64 | OK | Mar 28 2025 |
R-4.4-linux-x86_64 | OK | Mar 28 2025 |
Exports:default_fast_svget_default_fast_svget_default_general_svlatentlatent0logretparaparadensplotparatraceplotpredlatentpredvolapredypriorsruntimesampled_parametersspecify_priorssv_betasv_constantsv_exponentialsv_gammasv_infinitysv_inverse_gammasv_multinormalsv_normalsvbetasvlmsvlsamplesvlsample_rollsvsamplesvsample_fast_cppsvsample_general_cppsvsample_rollsvsample2svsimsvtausvtlsamplesvtlsample_rollsvtsamplesvtsample_rollthinningupdate_fast_svupdate_general_svupdate_regressorsupdate_t_errorupdatesummaryvalidate_and_process_expertvolavolplot
Dependencies:codalatticeRcppRcppArmadillo
Dealing with Stochastic Volatility in Time Series Using the R Package stochvol
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Started: 2013-10-22
Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol
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on Mar 28 2025.Last update: 2021-11-26
Started: 2020-11-03
Citation
To cite stochvol in publications use:
Hosszejni D, Kastner G (2021). “Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol.” Journal of Statistical Software, 100(12), 1–34. doi:10.18637/jss.v100.i12.
The original version of stochvol is documented here:
Kastner G (2016). “Dealing with Stochastic Volatility in Time Series Using the R Package stochvol.” Journal of Statistical Software, 69(5), 1–30. doi:10.18637/jss.v069.i05.
To refer to the sampling methodology used by the sampler without asymmetry (leverage) please cite:
Kastner G, Frühwirth-Schnatter S (2014). “Ancillarity-Sufficiency Interweaving Strategy (ASIS) for Boosting MCMC Estimation of Stochastic Volatility Models.” Computational Statistics & Data Analysis, 76, 408–423. doi:10.1016/j.csda.2013.01.002.
To refer to the sampling methodology used by the sampler that allows for asymmetry (leverage) please cite:
Hosszejni D, Kastner G (2019). “Approaches Toward the Bayesian Estimation of the Stochastic Volatility Model with Leverage.” In Argiento R, Durante D, Wade S (eds.), Bayesian Statistics and New Generations. BAYSM 2018, volume 296 series Springer Proceedings in Mathematics \& Statistics, 75–83. doi:10.1007/978-3-030-30611-3_8.
Corresponding BibTeX entries:
@Article{, title = {Modeling Univariate and Multivariate Stochastic Volatility in {R} with {stochvol} and {factorstochvol}}, author = {Darjus Hosszejni and Gregor Kastner}, journal = {Journal of Statistical Software}, year = {2021}, volume = {100}, number = {12}, pages = {1--34}, doi = {10.18637/jss.v100.i12}, }
@Article{, title = {Dealing with Stochastic Volatility in Time Series Using the {R} Package {stochvol}}, author = {Gregor Kastner}, journal = {Journal of Statistical Software}, year = {2016}, volume = {69}, number = {5}, pages = {1--30}, doi = {10.18637/jss.v069.i05}, }
@Article{, title = {Ancillarity-Sufficiency Interweaving Strategy ({ASIS}) for Boosting {MCMC} Estimation of Stochastic Volatility Models}, author = {Gregor Kastner and Sylvia Fr\"{u}hwirth-Schnatter}, journal = {Computational Statistics \& Data Analysis}, year = {2014}, volume = {76}, pages = {408--423}, doi = {10.1016/j.csda.2013.01.002}, }
@InProceedings{, title = {Approaches Toward the Bayesian Estimation of the Stochastic Volatility Model with Leverage}, author = {Darjus Hosszejni and Gregor Kastner}, booktitle = {Bayesian Statistics and New Generations. BAYSM 2018}, year = {2019}, series = {Springer Proceedings in Mathematics \& Statistics}, volume = {296}, pages = {75--83}, editor = {Raffaele Argiento and Daniele Durante and Sara Wade}, doi = {10.1007/978-3-030-30611-3_8}, publisher = {Springer}, address = {Cham}, }