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Dynamic correlation and equicorrelation analysis of global financial turmoil: evidence from emerging East Asian stock markets

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  • Xiao Jing Cai
  • Shuairu Tian
  • Shigeyuki Hamori

Abstract

This study investigates the dynamic conditional correlations (DCCs) between eight emerging East Asian stock markets and the US stock market and analyses the dynamic equicorrelation among these nine stock markets. We find a significant increase in the conditional correlations and equicorrelation in the first phase of the global financial crisis. We refer to this finding as contagion from the US stock market to the emerging East Asian markets. We also find an additional significant process of increasing correlations and equicorrelation (herding) in the second phase of the global financial crisis. Further, we employ two new models, namely DCCX-MGARCH (a DCC Multivariate GARCH model with exogenous variables) and DECOX-MGARCH (a dynamic equicorrelation multivariate GARCH model with exogenous variables), to identify the channels of contagion. We find that an increase in the VIX Index increases the conditional correlations and equicorrelation, while increases in TED spreads decrease the conditional correlations of six emerging East Asian countries with the USA. We compare the accuracy of the conditional correlation estimates of the DCC and DCCX models (or DECO and DECOX models) by constructing a loss function. We find that the DCCX (DECOX) model provides more accurate conditional correlation estimates than the DCC (DECO) model by extracting additional information from exogenous variables.

Suggested Citation

  • Xiao Jing Cai & Shuairu Tian & Shigeyuki Hamori, 2016. "Dynamic correlation and equicorrelation analysis of global financial turmoil: evidence from emerging East Asian stock markets," Applied Economics, Taylor & Francis Journals, vol. 48(40), pages 3789-3803, August.
  • Handle: RePEc:taf:applec:v:48:y:2016:i:40:p:3789-3803
    DOI: 10.1080/00036846.2016.1145349
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    9. Marco Tronzano, 2021. "Financial Crises, Macroeconomic Variables, and Long-Run Risk: An Econometric Analysis of Stock Returns Correlations (2000 to 2019)," JRFM, MDPI, vol. 14(3), pages 1-25, March.

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