Exposing volatility spillovers: A comparative analysis based on vector autoregressive models

Abstract

We present a comparative analysis of two empirical methods grounded on a common vector autoregressive framework. In this setting, we investigate the time-varying nature and direction of volatility spillovers between some major stock indexes spanning across Europe, China and US. We find evidence that drawing on partial Granger causality brings more robust results than relying on the information provided by generalized impulse responses, especially when there is uncertainty about what other relevant factors need to be modelled.