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News--Good or Bad--and Its Impact on Volatility Predictions over Multiple Horizons

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  • Xilong Chen
  • Eric Ghysels

Abstract

We introduce a new class of parametric models applicable to a mixture of high and low frequency returns and revisit the concept of news impact curves introduced by Engle and Ng (1993). Overall, we find that moderately good (intra-daily) news reduces volatility (the next day), while both very good news (unusual high intra-daily positive returns) and bad news (negative returns) increase volatility, with the latter having a more severe impact. The asymmetries disappear over longer horizons. Models featuring asymmetries dominate in terms of out-of-sample forecasting performance, especially during the 2007--2008 financial crisis. The Author 2010. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.

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  • Xilong Chen & Eric Ghysels, 2011. "News--Good or Bad--and Its Impact on Volatility Predictions over Multiple Horizons," The Review of Financial Studies, Society for Financial Studies, vol. 24(1), pages 46-81, October.
    • Handle: RePEc:oup:rfinst:v:24:y:2011:i:1:p:46-81
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