Paper 5 - C Review of Accounting Studies, 6, 305329, 2001...

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Review of Accounting Studies, 6, 305–329, 2001 ° C 2001 Kluwer Academic Publishers. Manufactured in The Netherlands. Back to Basics: Forecasting the Revenues of Internet Firms BRETT TRUEMAN trueman@haas.berkeley.edu Donald and Ruth Seiler Professor of Public Accounting, Haas School of Business, University of California, Berkeley, Berkeley, CA 94720-1900 M. H. FRANCO WONG Assistant Professor of Accounting, Haas School of Business, University of California, Berkeley, Berkeley, CA 94720-1900 XIAO-JUN ZHANG Assistant Professor of Accounting, Haas School of Business, University of California, Berkeley, Berkeley, CA 94720-1900 Abstract. This paper examines the roles played by past revenues, web usage data, and analysts in forecasting the future revenues of internet ±rms during the years 1998 to 2000. For this time period our analysis shows that estimates of web traf±c growth have signi±cant incremental value in the prediction of revenues above time-series forecasts. Furthermore, analysts almost always underestimate the revenues of internet ±rms. Historical revenue growth has incremental predictive power over analysts’ forecasts for portal and content/community ±rms, but not for our e-tailer sample. Moreover, the stocks of the portal and content/community ±rms 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 ±rms. However, perfect foreknowledge of actual web usage growth would provide incremental predictive power. Collectively, our ±ndings point to the potential value for forecasting purposes of both improving upon the web usage estimates and obtaining more timely reports of actual web traf±c. Keywords: analyst forecasts, forecasting, internet, revenues, web traf±c Forecasting revenues is an essential ±rst step in the valuation of any publicly traded company. This is especially true in the internet industry, where so few ±rms are reporting pro±ts and where investors and investment professionals have turned to the price/revenue ratio, rather than the price/earnings ratio, to measure relative valuations in the marketplace. 1 It is in this context that this paper examines the roles played by historical revenues, web usage data, and analysts in the prediction of the revenues of internet ±rms. 2 It is by no means an easy task to forecast internet ±rm revenues. The internet industry, and the ±rms within it, are so young that there is little historical ±nancial information available with which to generate forecasts—most of the ±rms in our sample have been public for two years or less. Moreover, these ±rms are evolving at such a rapid and unpredictable pace that past revenue numbers may have limited usefulness for forecasting purposes.
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Paper 5 - C Review of Accounting Studies, 6, 305329, 2001...

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