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Measuring and Testing the Impact of News on Volatility

Robert F. Engle and Victor K. Ng
The Journal of Finance
Vol. 48, No. 5 (Dec., 1993), pp. 1749-1778
Published by: Wiley for the American Finance Association
DOI: 10.2307/2329066
Stable URL: http://www.jstor.org/stable/2329066
Page Count: 30
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Measuring and Testing the Impact of News on Volatility
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Abstract

This paper defines the news impact curve which measures how new information is incorporated into volatility estimates. Various new and existing ARCH models including a partially nonparametric one are compared and estimated with daily Japanese stock return data. New diagnostic tests are presented which emphasize the asymmetry of the volatility response to news. Our results suggest that the model by Glosten, Jagannathan, and Runkle is the best parametric model. The EGARCH also can capture most of the asymmetry; however, there is evidence that the variability of the conditional variance implied by the EGARCH is too high.

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