Bayesian Multivariate GARCH Models

Fit Bayesian multivariate GARCH models using 'Stan' for full Bayesian inference. Generate (weighted) forecasts for means, variances (volatility) and correlations. Currently DCC(P,Q), CCC(P,Q), pdBEKK(P,Q), and BEKK(P,Q) parameterizations are implemented, based either on a multivariate gaussian normal or student-t distribution. DCC and CCC models are based on Engle (2002) and Bollerslev (1990) . The BEKK parameterization follows Engle and Kroner (1995) while the pdBEKK as well as the estimation approach for this package is described in Rast et al. (2020) . The fitted models contain 'rstan' objects and can be examined with 'rstan' functions.


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("bmgarch")

1.0.0 by Philippe Rast, a month ago


Report a bug at https://github.com/ph-rast/bmgarch/issues


Browse source code at https://github.com/cran/bmgarch


Authors: Philippe Rast [aut, cre] , Stephen Martin [aut]


Documentation:   PDF Manual  


Task views: Empirical Finance


GPL (>= 3) license


Imports rstan, rstantools, ggplot2, MASS, forecast, loo, Rdpack

Depends on methods, Rcpp

Suggests testthat

Linking to BH, Rcpp, RcppEigen, rstan, StanHeaders

System requirements: GNU make


See at CRAN