Linear and nonlinear intraday causalities in response to U.S. macroeconomic news announcements: Evidence from Central Europe

Abstract

This paper deals with an analysis of the information flow on and between three European stock markets operating in Frankfurt, Vienna, and Warsaw. We examine causal links between returns, volatility, and trading volume as well as the time of reaction to a news release and changes in the duration of causal interference. To model the conditional variance, we use the ARMA(1,1)-EGARCH-M(1,1) model. We investigate linear and nonlinear Granger causalities on the three stock exchanges using Bayesian large sample correction of the critical values in significance tests. The results of our study confirm the dominant role of the Frankfurt Stock Exchange, since the most significant linear relationship is the causality running from DAX30 returns to the returns of the ATX20 and WIG20 (which exists irrespective of the time of the day, presence of important public news, and lag length of the underlying VAR models). Moreover, the empirical results of this paper confirm the strong impact of announcements of macroeconomic news from the U.S. economy on the structure of both linear and nonlinear causal links on the three markets under study.