Long and short-term dynamic interactions between major international stock markets and the Malaysian stock market

Abstract

This paper considers an investigation of the dynamic causal linkages amongst 8 international stock price indexes using a daily data set. We consider 4 major established markets and 4 Asian emerging stock markets in the same system. Causal transmission patterns are examined using recent methods of (i) vector error- correction modeling and (ii) level VAR modeling with possibly integrated and cointegrated processes, advocated by (i) Toda and Phillips (1993a) and (ii) Toda and Yamamoto (1995). The paper illustrates how such methods may be appropriately augmented in a compatible fashion to unearth previously unfounded linkage properties inherent amongst a system of stock price indexes. In particular, we demonstrate that previous research, by using ordinary difference VARS, ignored an important component of linkages displayed purely over the long run. This essentially untapped evidence provides robust and very useful information to international financial analysts and investors. At a substantive level, results of this study tend to support the contention offered by several studies in the literature of significant short and long term relationships between established OECD and Asian markets and also the leadership of the US over both short and long-run. The levels VAR confirms the US market's influential leadership over the long run. At the regional level in Southeast Asia, the results tend to confirm, as expected, the leading role of Hongkong. And consistent with the recent financial crisis in this region, the results tend to lend strong support to the view that stock price fluctuations in all these Asian markets are explained mostly by their regional markets (rather than the advanced markets). At a methodological level, this analysis also provides a primer for the wealth of applied financial econometric research focusing on dynamic causal inference which involve systems containing possibly integrated and cointegrated processes.