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stochvol (version 3.2.6)

Efficient Bayesian Inference for Stochastic Volatility (SV) Models

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) and Hosszejni and Kastner (2019) ; the most common use cases are described in Hosszejni and Kastner (2021) and Kastner (2016) and the package examples.

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Version

Install

install.packages('stochvol')

Monthly Downloads

1,627

Version

3.2.6

License

GPL (>= 2)

Maintainer

Darjus Hosszejni

Last Published

July 31st, 2025

Functions in stochvol (3.2.6)

extractors

Common Extractors for 'svdraws' and 'svpredict' Objects
svsim

Simulating a Stochastic Volatility Process
sv_constant

Prior Distributions in stochvol
svsample_roll

Rolling Estimation of Stochastic Volatility Models
svsample_fast_cpp

Bindings to C++ Functions in stochvol
specify_priors

Specify Prior Distributions for SV Models
update_general_sv

Single MCMC Update Using General SV
svsample

Markov Chain Monte Carlo (MCMC) Sampling for the Stochastic Volatility (SV) Model
update_fast_sv

Single MCMC Update Using Fast SV
svlm

Markov Chain Monte Carlo (MCMC) Sampling for the Stochastic Volatility (SV) Model
stochvol-package

Efficient Bayesian Inference for Stochastic Volatility (SV) Models
validate_and_process_expert

Validate and Process Argument 'expert'
update_t_error

Single MCMC update to Student's t-distribution
update_regressors

Single MCMC update of Bayesian linear regression
updatesummary

Updating the Summary of MCMC Draws
volplot

Plotting Quantiles of the Latent Volatilities
paratraceplot

Trace Plot of MCMC Draws from the Parameter Posteriors
get_default_fast_sv

Default Values for the Expert Settings
logret

Computes the Log Returns of a Time Series
plot.svdraws

Graphical Summary of the Posterior Distribution
predict.svdraws

Prediction of Future Returns and Log-Volatilities
plot.svpredict

Graphical Summary of the Posterior Predictive Distribution
paradensplot

Probability Density Function Plot for the Parameter Posteriors
exrates

Euro exchange rate data
paratraceplot.svdraws

Trace Plot of MCMC Draws from the Parameter Posteriors