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

  • Xilong Chen
  • Eric Ghysels
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    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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    File URL: http://hdl.handle.net/10.1093/rfs/hhq071
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    Article provided by Society for Financial Studies in its journal Review of Financial Studies.

    Volume (Year): 24 (2011)
    Issue (Month): 1 (October)
    Pages: 46-81

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    Handle: RePEc:oup:rfinst:v:24:y:2011:i:1:p:46-81
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