Heavy-Tailed Innovations in the R Package stochvol

We document how sampling from a conditional Student's t distribution is implemented in stochvol. Moreover, a simple example using EUR/CHF exchange rates illustrates how to use the augmented sampler. We conclude with results and implications. (author's abstract)

[1]  Yasuhiro Omori,et al.  Stochastic volatility model with leverage and asymmetrically heavy-tailed error using GH skew Student's t-distribution , 2012, Comput. Stat. Data Anal..

[2]  S. Chib,et al.  Bayes inference in regression models with ARMA (p, q) errors , 1994 .

[3]  Florian Huber.  Density forecasting using Bayesian global vector autoregressions with stochastic volatility , 2016 .

[4]  N. Shephard,et al.  Multivariate stochastic variance models , 1994 .

[5]  Helio S. Migon,et al.  The extended generalized inverse Gaussian distribution for log-linear and stochastic volatility models , 2006 .

[6]  Mark J. Jensen,et al.  Bayesian Semiparametric Stochastic Volatility Modeling , 2008 .

[7]  Florian Huber,et al.  Does Joint Modelling of the World Economy Pay Off? Evaluating Multivariate Forecasts from a Bayesian GVAR , 2015 .

[8]  S. Frühwirth-Schnatter,et al.  Analysis of Exchange Rates via Multivariate Bayesian Factor Stochastic Volatility Models , 2014 .

[9]  J. Griffin,et al.  Bayesian Nonparametric Modelling of the Return Distribution with Stochastic Volatility , 2010 .

[10]  Gregor Kastner,et al.  Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models , 2014, Comput. Stat. Data Anal..

[11]  S. Frühwirth-Schnatter,et al.  Bayesian inference for finite mixtures of univariate and multivariate skew-normal and skew-t distributions. , 2010, Biostatistics.

[12]  Gregor Kastner,et al.  Dealing with Stochastic Volatility in Time Series Using the R Package stochvol , 2016, 1906.12134.

[13]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[14]  N. Shephard,et al.  Markov chain Monte Carlo methods for stochastic volatility models , 2002 .