Dealing with Stochastic Volatility in Time Series Using the R Package stochvol

Dealing with Stochastic Volatility in Time Series Using the R Package stochvol

The R package stochvol provides a fully Bayesian implementation of heteroskedasticity modeling within the framework of stochastic volatility. It utilizes Markov chain Monte Carlo (MCMC) samplers to conduct inference by obtaining draws from the posterior distribution of parameters and latent variable...

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Bibliographic Details
Main Author: Gregor Kastner
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2016-02-01
Series:Journal of Statistical Software
Subjects:
Bayesian inference
Markov chain Monte Carlo (MCMC)
auxiliary mixture sampling
ancillarity-sufficiency interweaving strategy (ASIS)
state-space model
heteroskedasticity
financial time series
Online Access:https://www.jstatsoft.org/index.php/jss/article/view/2559

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https://www.jstatsoft.org/index.php/jss/article/view/2559

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