Estimating and Explaining Extreme Comovements in Asia-Pacific Equity Markets

Abstract

The correlation structure amongst selected Asia-Pacific equity markets is examined using the Constant Correlation multivariate GARCH (CC-MGARCH) model, the Dynamic Conditional Correlation multivariate GARCH (DCC-MGARCH) model, and an Exponentially-Weighted Moving Average (EWMA) correlation measure. The markets of Australia, Hong Kong, Japan and Singapore are analyzed from 1990 to 2001 and dynamic nature of the correlation is captured and explained. We find that global as well as regional factors contribute to the correlation spikes. Extreme volatility does not necessarily result in extreme correlations between some markets and there is higher comovement between markets since the Asian financial crisis. We also find that despite common periods of high volatility, there is still economic justification for diversification within this region.

Trend Analysis of Global Stock Market Linkage Based on a Dynamic Conditional Correlation Network

“…The biggest characteristic of the DCC model is that the correlation coefficient is the dynamic correlation coefficient which changes over time. There are many scholars who apply the model to analyze the dynamic relationship between economic indicators and financial assets to explore the internal mechanism of economic phenomena (Chandra 2005;Aslanidis et al 2010).…”