Back to Basics: Forecasting the Revenues of Internet Firms

Back to Basics: Forecasting the Revenues of Internet Firms This paper examines the roles played by past revenues, web usage data, and analysts in forecasting the future revenues of internet firms during the years 1998 to 2000. For this time period our analysis shows that estimates of web traffic growth have significant incremental value in the prediction of revenues above time-series forecasts. Furthermore, analysts almost always underestimate the revenues of internet firms. Historical revenue growth has incremental predictive power over analysts' forecasts for portal and content/community firms, but not for our e-tailer sample. Moreover, the stocks of the portal and content/community firms with high historical revenue growth earn higher abnormal returns during our sample period than do those with low historical growth. Estimates of web usage growth generally do not have incremental value over analysts' forecasts for predicting the revenues of either set of firms. However, perfect foreknowledge of actual web usage growth would provide incremental predictive power. Collectively, our findings point to the potential value for forecasting purposes of both improving upon the web usage estimates and obtaining more timely reports of actual web traffic. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Accounting Studies Springer Journals

Back to Basics: Forecasting the Revenues of Internet Firms

Loading next page...
 
/lp/springer_journal/back-to-basics-forecasting-the-revenues-of-internet-firms-jUW6b0KBy7
Publisher
Springer Journals
Copyright
Copyright © 2001 by Kluwer Academic Publishers
Subject
Business and Management; Accounting/Auditing; Corporate Finance; Public Finance
ISSN
1380-6653
eISSN
1573-7136
D.O.I.
10.1023/A:1011623111051
Publisher site
See Article on Publisher Site

Abstract

This paper examines the roles played by past revenues, web usage data, and analysts in forecasting the future revenues of internet firms during the years 1998 to 2000. For this time period our analysis shows that estimates of web traffic growth have significant incremental value in the prediction of revenues above time-series forecasts. Furthermore, analysts almost always underestimate the revenues of internet firms. Historical revenue growth has incremental predictive power over analysts' forecasts for portal and content/community firms, but not for our e-tailer sample. Moreover, the stocks of the portal and content/community firms with high historical revenue growth earn higher abnormal returns during our sample period than do those with low historical growth. Estimates of web usage growth generally do not have incremental value over analysts' forecasts for predicting the revenues of either set of firms. However, perfect foreknowledge of actual web usage growth would provide incremental predictive power. Collectively, our findings point to the potential value for forecasting purposes of both improving upon the web usage estimates and obtaining more timely reports of actual web traffic.

Journal

Review of Accounting StudiesSpringer Journals

Published: Oct 3, 2004

References

  • Tests of Analysts' Overreaction/Underreaction to Earnings Information as an Explanation for Anomalous Stock Price Behavior
    Abarbanell, J.; Bernard, V.

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