Fast and accurate variational inference for large Bayesian VARs with stochastic volatility

Joshua Chan and Xuewen Yu ()

CAMA Working Papers from Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University

Abstract: We propose a new variational approximation of the joint posterior distribution of the log-volatility in the context of large Bayesian VARs. In contrast to existing approaches that are based on local approximations, the new proposal provides a global approximation that takes into account the entire support of the joint distribution. In a Monte Carlo study we show that the new global approximation is over an order of magnitude more accurate than existing alternatives. We illustrate the proposed methodology with an application of a 96-variable VAR with stochastic volatility to measure global bank network connectedness. Our measure is able to detect the drastic increase in global bank network connectedness much earlier than rolling-window estimates from a homoscedastic VAR.

Keywords: large vector autoregression; stochastic volatility; Variational Bayes; volatility network; connectedness (search for similar items in EconPapers)
JEL-codes: C11 C32 C55 G21 (search for similar items in EconPapers)
Pages: 36 pages
Date: 2020-12
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-net and nep-ore
References: Add references at CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
https://cama.crawford.anu.edu.au/sites/default/fil ... 108_2020_chan_yu.pdf (application/pdf)

Related works:
Journal Article: Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility (2022)
Working Paper: Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility (2022)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:een:camaaa:2020-108

Access Statistics for this paper

More papers in CAMA Working Papers from Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University Contact information at EDIRC.
Bibliographic data for series maintained by Cama Admin ().