Volatility interdependency: a quantile regression analysis in Asian stock markets
Neha Seth and
Laxmidhar Panda
Afro-Asian Journal of Finance and Accounting, 2020, vol. 10, issue 3, 409-429
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.
Keywords: financial contagion; volatility interdependence; quantile regression; Asian stock markets; global financial crisis; European debt crisis. (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=108247 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ids:afasfa:v:10:y:2020:i:3:p:409-429
Access Statistics for this article
More articles in Afro-Asian Journal of Finance and Accounting from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().