We test the importance of multivariate information for modelling and forecasting inflation’s conditional mean and variance. In the literature, the existence of inflation’s conditional heteroskedasticity has been debated for years, as it seemed to appear only in some datasets and for some lag lengths. This phenomenon might be due to the fact that inflation depends on a linear combination of econ...

Multivariate GARCH (MGARCH) models are usually estimated under multivariate normality. In this paper, for non-elliptically distributed financial returns, we propose copula-based multivariate GARCH (C-MGARCH) model with uncorrelated dependent errors, which are generated through a linear combination of dependent random variables. The dependence structure is controlled by a copula function. Our ne...

Most studies on the asymmetric and non-linear properties of US business cycles exclude the dimension of asymmetric conditional volatility. Engle (1982) proposes an autoregressive conditional heteroskedasticity (ARCH) model to capture the time-varying volatility of inflation rates in the United Kingdom. Weiss (1984) finds evidence of ARCH in the US industrial production. The ARCH model is then e...

The BEKK model is a popular multivariate GARCH processes. The paper develops a new general asymmetric BEKK structure, which is based on recent empirical findings by semi-parametric news impact curves. For estimating the new model, a Markov chain Monte Carlo technique is used. Empirical results for triviarte asset returns from firms in the US indicate that the deviance information criterion favo...

Multivariate models of asset returns are very important in financial applications. Asset allocation, risk assessment and construction of an optimal portfolio require estimates of the covariance matrix between the returns of assets (see e.g. Aguilar and West (2000), Pajor (2005a, 2005b)). Similarly, hedges require a covariance matrix of all the assets in the hedge. There are two main types of vo...

We examine the effect of oil price uncertainty on sovereign credit risks in Gulf Cooperation Council (GCC) countries. Unlike past studies, we employ a structural vector autoregression with multivariate GARCH-in-mean (VAR-GARCH-in-mean) approach after filtering out outliers observed series. The findings show that market has positive impact Credit Default Swap (CDS) spreads GCC Furthermore, find ...

Exponential models of Autoregressive Conditional Heteroscedasticity (ARCH) are of special interest, since they enable richer dynamics (e.g. contrarian or cyclical), provide greater robustness to jumps and outliers, and guarantee the positivity of volatility. The latter is not guaranteed in ordinary ARCH models, in particular when additional exogenous and/or predetermined variables (“X”) are inc...