Publication . Article . 2019

GOOD NEWS, BAD NEWS AND GARCH EFFECTS IN STOCK RETURN DATA

Name: GOOD NEWS, BAD NEWS AND GARCH EFFECTS IN STOCK RETURN DATA
Creator: Depken, Craig A.
Keywords: jel:C32, jel:G14, information flows; autocorrelation, General Economics, Econometrics and Finance, Stock return, Autoregressive conditional heteroskedasticity, Autocorrelation, Economics, Econometrics, Sample (statistics)

Depken, Craig A.;

Open Access

doi: 10.1080/15140326.2001.12040567

Published: 21 Jan 2019 Journal: Journal of Applied Economics, volume 4, issue November, pages 313-327

- Summary
- References
  (10)

Abstract

It is shown that the volume of trade can be decomposed into proportional proxies for stochastic flows of good news and bad news into the market. Positive (good) information flows are assumed to increase the price of a financial vehicle while negative (bad) information flows decrease the price. For the majority of a sample of ten split-stocks it is shown that the proposed decomposition explains more GARCH than volume itself. Using the proposed decomposition, the variance of returns for younger split stocks reacts asymmetrically to good news flowing into the market, while the variance for older split-stocks reacts symmetrically to good news and bad news.

Subjects by Vocabulary

JEL Classification: jel:C32 jel:G14

Microsoft Academic Graph classification: Stock return Autoregressive conditional heteroskedasticity Autocorrelation Economics Econometrics Sample (statistics) Variance (accounting)

Subjects

information flows; autocorrelation, General Economics, Econometrics and Finance

Related Organizations

The University of Texas at Arlington
United States

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