Characteristics of Earnings-Leading Versus Price-Leading Firms

Characteristics of Earnings-Leading Versus Price-Leading Firms This study attempts to identify firm characteristics that explain the disparity between the information content of accounting earnings and stock prices. Granger's causality concept was employed to classify sample firms into four groups: price-leading firms, feedback-system firms, earnings-leading firms, and no-causation firms. The feedback-system firms were either combined with the no-causation firms or eliminated entirely to form three sample groups. The entire sample firms then were divided into two classes. The first is for estimation, and the second is for prediction. Results indicate that firm size, capital structure, R-square of regressing prices at time t against earnings at time t − 1, R-square of regressing earnings at time t against prices at time t − 1, and percentage of shares held by institutions are the significant explaining variables. The application of the coefficient estimates to the hold-out sample indicates that 76.2% of the firms can be correctly classified into the corresponding groups. These results were consistent with those from canonical discrimination and other multivariate statistical methods. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Quantitative Finance and Accounting Springer Journals

Characteristics of Earnings-Leading Versus Price-Leading Firms

Loading next page...
 
/lp/springer_journal/characteristics-of-earnings-leading-versus-price-leading-firms-qAknTLTNHK
Publisher
Kluwer Academic Publishers
Copyright
Copyright © 1997 by Kluwer Academic Publishers
Subject
Finance; Corporate Finance; Accounting/Auditing; Econometrics; Operation Research/Decision Theory
ISSN
0924-865X
eISSN
1573-7179
D.O.I.
10.1023/A:1008210904315
Publisher site
See Article on Publisher Site

Abstract

This study attempts to identify firm characteristics that explain the disparity between the information content of accounting earnings and stock prices. Granger's causality concept was employed to classify sample firms into four groups: price-leading firms, feedback-system firms, earnings-leading firms, and no-causation firms. The feedback-system firms were either combined with the no-causation firms or eliminated entirely to form three sample groups. The entire sample firms then were divided into two classes. The first is for estimation, and the second is for prediction. Results indicate that firm size, capital structure, R-square of regressing prices at time t against earnings at time t − 1, R-square of regressing earnings at time t against prices at time t − 1, and percentage of shares held by institutions are the significant explaining variables. The application of the coefficient estimates to the hold-out sample indicates that 76.2% of the firms can be correctly classified into the corresponding groups. These results were consistent with those from canonical discrimination and other multivariate statistical methods.

Journal

Review of Quantitative Finance and AccountingSpringer Journals

Published: Sep 29, 2004

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off