Measuring and Testing the Impact of News on Volatility

2.3kCitations
Citations of this article
559Readers
Mendeley users who have this article in their library.

This article is free to access.

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. 1993 The American Finance Association

References Powered by Scopus

13497Citations
3057Readers
Get full text
Get full text

This article is free to access.

Cited by Powered by Scopus

This article is free to access.

New introduction to multiple time series analysis

3475Citations
2576Readers
Get full text
1405Citations
664Readers
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

ENGLE, R. F., & NG, V. K. (1993). Measuring and Testing the Impact of News on Volatility. The Journal of Finance, 48(5), 1749–1778. https://doi.org/10.1111/j.1540-6261.1993.tb05127.x

Readers over time

‘09‘10‘11‘12‘13‘14‘15‘16‘17‘18‘19‘20‘21‘22‘23‘24‘25020406080

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 228

71%

Professor / Associate Prof. 34

11%

Researcher 33

10%

Lecturer / Post doc 26

8%

Readers' Discipline

Tooltip

Economics, Econometrics and Finance 216

63%

Business, Management and Accounting 87

25%

Mathematics 23

7%

Computer Science 16

5%

Article Metrics

Tooltip
Mentions
References: 3

Save time finding and organizing research with Mendeley

Sign up for free
0