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Volatility interdependency: a quantile regression analysis in Asian stock markets

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  • Neha Seth
  • Laxmidhar Panda

Abstract

The purpose of this paper to investigate the structure of volatility interdependency among the Asian stock markets during the period of the global financial crisis (GFC) and the European sovereign debt crisis (ESDC). This paper uses quantile regression (QR) technique in the conditional volatility series obtained from the result of ARIMA (p, q)-GARCH (1, 1) model. The sample includes eight emerging and three developed stock markets covering the period from 2nd January 2000 to 31st March 2016. The results of the QR model strongly support volatility interdependency among the Asian stock markets during the period of financial crisis. The results of this paper also indicated that emerging markets are majorly affected by conditional volatility generated from developed markets in periods of financial crisis. This paper provides valuable information regarding the complex volatility structure among the Asian stock markets during the crisis period which may help to domestic and foreign investors in taking major decisions on portfolio diversification during periods of global financial turbulence.

Suggested Citation

  • Neha Seth & Laxmidhar Panda, 2020. "Volatility interdependency: a quantile regression analysis in Asian stock markets," Afro-Asian Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 10(3), pages 409-429.
    • Handle: RePEc:ids:afasfa:v:10:y:2020:i:3:p:409-429
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