Cross-sectional return dispersion and volatility prediction

Tools

Fei, Tianlun, Liu, Xiaoquan and Wen, Conghua (2019) Cross-sectional return dispersion and volatility prediction. Pacific-Basin Finance Journal, 58 . p. 101218. ISSN 0927-538X

[thumbnail of CSD.pdf]
Preview
 PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Available under Licence Creative Commons Attribution.
Download (1MB) | Preview

Abstract

We use intraday and daily data to examine the impact of cross-sectional return dispersion on volatility forecasting in the Chinese equity market. We adopt the GARCH, GJR-GARCH, and HAR models and, by augmenting them with return dispersion measures, provide empirical evidence that the return dispersion exhibits substantial information in describing the volatility dynamics by generating signicantly lower forecasting errors at market and industry levels. Furthermore, the information content of the return dispersion tends to o er economic gain to a mean-variance

utility investor. The ndings are robust with respect to alternative volatility proxies, subsample analysis, and alternative market-wide stock indices.

Item Type: Article
Keywords: Industry Effect; Chinese CSI Index; Herding; Financial Markets.
Schools/Departments: University of Nottingham Ningbo China > Faculty of Science and Engineering > School of Mathematical Sciences
Identification Number: 10.1016/j.pacfin.2019.101218
Depositing User: Zhou, Elsie
Date Deposited: 11 Dec 2019 01:33
Last Modified: 11 Dec 2019 01:33
URI: https://eprints.nottingham.ac.uk/id/eprint/59531

Actions (Archive Staff Only)

Edit View Edit View