Measuring and Testing the Impact of News on Volatility.

This paper defines the news impact curve that 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 that emphasize the asymmetry of the volatility response to news. The authors' results suggest that the model by L. Glosten, R. Jagannathan, and D. Runkle (1989) 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. Copyright 1993 by American Finance Association.