Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets

Testing for constant hedge ratios in commodity markets: a multivariate GARCH approach

We develop a new multivariate generalized ARCH (GARCH) parameterization suitable for testing the hypothesis that the optimal futures hedge ratio is constant over time, given that the joint distribution of cash and futures prices is characterized by autoregressive conditional heteroskedasticity (ARCH). The advantage of the new parameterization is that it allows for a flexible form of time-varyin...

Multivariate Regime–Switching GARCH with an Application to International Stock Markets

We develop a multivariate generalization of the Markov–switching GARCH model introduced by Haas, Mittnik, and Paolella (2004b) and derive its fourth– moment structure. An application to international stock markets illustrates the relevance of accounting for volatility regimes from both a statistical and economic perspective, including out–of–sample portfolio selection and computation of Value– ...

Comparison of Multivariate GARCH Models with Application to Zero-Coupon Bond Volatility

The purpose of this thesis is to investigate different formulations of multivariate GARCH models and to apply two of the popular ones – the BEKKGARCH model and the DCCGARCH model – in evaluating the volatility of a portfolio of zero-coupon bonds. Multivariate GARCH models are considered as one of the most useful tools for analyzing and forecasting the volatility of time series when volatility f...

Volatility spillovers across equity markets: European evidence

This paper examines the issue of volatility spillovers across the three largest European stock markets, namely London, Frankfurt and Paris. The Exponential Generalized Autoregressive Conditional Heteroscedasticity model is used to capture potential asymmetric effects of innovations on volatility. During the period from 01/01/84 to 07/12/93, reciprocal spillovers are found to exist between Londo...

Transmission of Returns and Volatility in Art Markets: A Multivariate GARCH Analysis