three US financial assets, we compare the realized MEGARCH models with existing multivariate GARCH class models. The …The paper develops a new realized matrix-exponential GARCH (MEGARCH) model, which uses the information of returns and … realized measure of co-volatility matrix simultaneously. The paper also considers an alternative multivariate asymmetric …

We develop Bayesian techniques for estimation and model comparison in a novel Generalised Stochastic Unit Root (GSTUR …

development of adjacent age groups is assured allowing for consistent forecasts. We develop an appropriate Markov Chain Monte … Carlo algorithm to estimate the parameters and the latent variables in an efficient one-step procedure. Via the Bayesian …

This paper develops Bayesian econometric methods for posterior inference in non-parametric mixed frequency VARs using …

approach using a Bayesian MS-VAR which is net of these arbitrary components. This method allows for the consistent … method on artificial as well a real data and conduct an empirical backtest, in which generated scenarios are compared to the … actual development during the financial crisis. The method is challenged with the DSGE model and conditional forecasting. …

This paper develops Bayesian econometric methods for posterior inference in non-parametric mixed frequency VARs using …

This note presents the R package bayesGARCH (Ardia, 2007) which provides functions for the Bayesian estimation of the … parsimonious and effective GARCH(1,1) model with Student-t innovations. The estimation procedure is fully automatic and thus avoids …

. A state-dependent volatility spillover GARCH hedging strategy is developed to capture the regime switching global equity …

using Bayesian methods. In particular, the implications on the forecast and impulse response function distributions of …