Affiliation:
1. Aalborg University Business School Aalborg Universitet Aalborg Denmark
2. Department of Accounting and Finance University of Greenwich London UK
Abstract
AbstractIn this article, we investigate the pattern and dynamics of return and volatility connectedness across East and Southeast Asian markets (referred to as the ASEAN5 + 5 group) by utilizing forecast‐error variance decompositions in a generalized VAR framework in conjunction with the Bai‐Perron procedure to control for structural breaks. Our analysis of the dynamics of return spillovers in static and time‐varying settings identifies that the stock markets of Singapore, Hong Kong and South Korea act as constant and largest net transmitters of shocks throughout the period from January 2003 to July 2021. The Chinese stock market is found to have the lowest return connectedness with other regional markets, which could be due to the local foreign ownership regulations. Visualization of the net pairwise return spillover network shows that Singapore is the sole net transmitter of shocks to all other markets in the ASEAN5 + 5 group, whereas, China, despite its market size is the sole net recipient. Two other markets in the regional group are identified as the net receivers, Japan and the Philippines, with the former becoming a net recipient from 2007. Our analysis of structural breaks shows that return spillovers across the markets intensify during periods of economic turmoil, financial shocks and the health crisis (COVID‐19), however, return to the pre‐shock levels during stable market periods. Further analysis of time‐varying patterns revealed that the dynamic connectedness across the region is not symmetrical and the influence of negative returns is more pronounced. The investigation of volatility spillovers shows no substantial differences. The stock markets generally retain their roles. Importantly, the time‐varying volatility connectedness exhibits similar patterns and tends to reach peak levels during turbulent episodes.
Subject
Economics and Econometrics,Finance
Cited by
1 articles.
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