The comovements of tail risks in time and frequency domains: evidence from US and emerging Asian stock markets

Abstract

Abstract The study applies the wavelet local multiple correlations to investigate the level of comovements among the tail risks of US and emerging Asian stock markets in both time and frequency domains. Through this empirical investigation, we address the question of how the transmission of tail risk across the concerned stock markets is changing over specific timescales, varying from short term to long term. Empirical results from the multivariate time–frequency correlations show that the comovements of tail risks are distinctively higher during periods of economic and political turmoil in the short term. The multivariate long-term comovements are highly stable and extremely strong which can be taken as evidence of long-term integration. In contrast, the bivariate time–frequency correlations are remarkably weaker in the short term not only during periods of crises but over most of the sample period. The results of the bivariate analysis also highlight the instability of the long-term pairwise correlations of the tail risks, showing that it is susceptible to sudden changes, which indicates that the tail risks of the US and emerging Asian stock markets are actually not completely integrated in the long term. This finding also implies that the tail risks of US and emerging Asian stock markets are nonlinearly connected in the long term.

Keywords

• Stock markets
• Value at risk
• Tail risk
• Multiple local correlations
• Wavelet analysis
• USA