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

DOI10.1016/j.jedc.2022.104505OpenAlexW4289443855MaRDI QIDQ2097996

Xuewen Yu, Joshua C. C. Chan

Publication date: 17 November 2022

Published in: Journal of Economic Dynamics \& Control (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2206.08438

zbMATH Keywords

connectednessstochastic volatilityvariational Bayeslarge vector autoregressionvolatility network

Mathematics Subject Classification ID

Game theory, economics, finance, and other social and behavioral sciences (91-XX)

Related Items (1)

Variational Bayes in State Space Models: Inferential and Predictive Accuracy

Uses Software

• bvarsv

Cites Work

• Unnamed Item
• Unnamed Item
• Bayesian Multivariate Time Series Methods for Empirical Macroeconomics
• Hierarchical shrinkage priors for regression models
• An introduction to variational methods for graphical models
• Reducing the state space dimension in a large TVP-VAR
• Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors
• On the adaptive elastic net with a diverging number of parameters
• On the network topology of variance decompositions: measuring the connectedness of financial firms
• Large time-varying parameter VARs
• Real-Time Density Forecasts From Bayesian Vector Autoregressions With Stochastic Volatility
• Explaining Variational Approximations
• Multivariate Stochastic Variance Models
• Bayesian Vector Autoregressions with Stochastic Volatility
• Likelihood analysis of non-Gaussian measurement time series
• Monte Carlo maximum likelihood estimation for non-Gaussian state space models
• Dirichlet–Laplace Priors for Optimal Shrinkage
• Time Varying Structural Vector Autoregressions and Monetary Policy

This page was built for publication: Fast and accurate variational inference for large Bayesian VARs with stochastic volatility