Large Bayesian vector autoregressions with various forms of stochastic volatility have
become increasingly popular in empirical macroeconomics. One main difficulty for …

Estimation and prediction in high dimensional multivariate factor stochastic volatility models
is an important and active research area, because such models allow a parsimonious …

A Maximum Likelihood recursive state estimator is derived for non-linear state–space
models. The estimator iteratively combines a particle filter to generate the predicted/filtered …

This paper studies the empirical effects of legal challenges to monetary policy. Several
policy measures of the European Central Bank have come under scrutiny before national …

To account for asymmetric dependence in extreme events, we propose a dynamic
generalized hyperbolic skew Student-t factor copula where the factor loadings follow …

This paper expands traditional stochastic volatility models by allowing for time-varying
skewness without imposing it. While dynamic asymmetry may capture the likely direction of …

High-dimensional matrix-valued time series are of significant interest in economics and
finance, with prominent examples including cross region macroeconomic panels and firms' …

Estimation and prediction in high dimensional multivariate factor stochastic volatility models
is an important and active research area because such models allow a parsimonious …

This paper explores factors that drive the volatility structure of New Zealand stock trade
levels, with the aim of understanding unusual volatility of stock trade levels that may pose a …

This paper proposes factor stochastic volatility models with skew error distributions. The
generalized hyperbolic skew t-distribution is employed for common-factor processes and …