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Measuring and Testing the Impact of News on Volatility

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Author Info
 Engle, Robert F
Ng, Victor K

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Abstract

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.

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Article provided by American Finance Association in its journal Journal of Finance.

Volume (Year): 48 (1993)
Issue (Month): 5 (December)
Pages: 1749-78
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Handle: RePEc:bla:jfinan:v:48:y:1993:i:5:p:1749-78

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Francis Dieobold, 1986. "Modeling The persistence Of Conditional Variances: A Comment," Econometric Reviews, Taylor and Francis Journals, vol. 5(1), pages 51-56. [Downloadable!] (restricted)
  2. Schwert, G William, 1990. "Stock Volatility and the Crash of '87," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 3(1), pages 77-102. [Downloadable!] (restricted)
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  3. Matthew L. Higgins & Anil K. Bera, 1990. "A Class of Nonlinear Arch Models," University of California at San Diego, Economics Working Paper Series 90-40, Department of Economics, UC San Diego.
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  4. Pagan, Adrian R. & Schwert, G. William, 1990. "Alternative models for conditional stock volatility," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 267-290. [Downloadable!] (restricted)
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  5. Anil K. Bera & Sangkyu Lee & Matthew L. Higgins, 1990. "On the Formulation of A General Structure for Conditional Heteroskedasticity," University of California at San Diego, Economics Working Paper Series 90-41, Department of Economics, UC San Diego.
  6. Gourieroux, C. & Monfort, A., 1990. "Qualitative Threshold Arch Models," Working Papers 9009, Centre de Recherche en Economie et Statistique.
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  7. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September. [Downloadable!] (restricted)
  8. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59. [Downloadable!] (restricted)
  9. Tim Bollerslev & Jeffrey M. Wooldridge, 1988. "Quasi-Maximum Likelihood Estimation of Dynamic Models with Time-Varying Covariances," Working papers 505, Massachusetts Institute of Technology (MIT), Department of Economics.
  10. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April. [Downloadable!] (restricted)
  11. Robert Engle & Tim Bollerslev, 1986. "Modelling the persistence of conditional variances," Econometric Reviews, Taylor and Francis Journals, vol. 5(1), pages 1-50. [Downloadable!] (restricted)
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