Measuring and Testing the Impact of News on Volatility

32 Pages Posted: 18 Jun 2004 Last revised: 23 Jan 2022

See all articles by Robert F. Engle

Robert F. Engle

New York University (NYU) - Department of Finance; National Bureau of Economic Research (NBER); New York University (NYU) - Volatility and Risk Institute

Victor K. Ng

International Monetary Fund (IMF) - Research Department; National Bureau of Economic Research (NBER)

Date Written: April 1991

Abstract

This paper introduces the News Impact Curve to measure how new information is incorporated into volatility estimates. A variety of new and existing ARCH models are compared and estimated with daily Japanese stock return data to determine the shape of the News Impact Curve. New diagnostic tests are presented which emphasize the asymmetry of the volatility response to news. A partially non-parametric ARCH model is introduced to allow the data to estimate this shape. A comparison of this model with the existing models suggests that the best models are one by Glosten Jaganathan and Runkle (GJR) and Nelson's EGARCE. Similar results hold on a pre-crash sample period but are less strong.

Suggested Citation

Engle, Robert F. and Ng, Victor K., Measuring and Testing the Impact of News on Volatility (April 1991). NBER Working Paper No. w3681, Available at SSRN: https://ssrn.com/abstract=262096

Robert F. Engle (Contact Author)

New York University (NYU) - Department of Finance ( email )

Stern School of Business
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National Bureau of Economic Research (NBER) ( email )

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New York University (NYU) - Volatility and Risk Institute ( email )

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Victor K. Ng

International Monetary Fund (IMF) - Research Department ( email )

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National Bureau of Economic Research (NBER)

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