Please use this identifier to cite or link to this item:
http://hdl.handle.net/11375/5360
Title: | Web-based metrics and internet stock prices |
Authors: | Bontis, Nick Mill, Jason McMaster University, Michael G. DeGroote School of Business, Management of Innovation and New Technology Research Centre |
Publication Date: | Jan-2000 |
Series/Report no.: | Working paper (Michael G. DeGroote School of Business. Management of Innovation and New Technology Research Centre) no. 93 |
Abstract: | <p>The use of web-site metrics such as "number of page hits" is very popular. Web-site counters are widely used on personal home pages and corporate sites but offer little insight into the value created by investing in a web presence. The search for more effective web metrics is important to companies that are betting their entire business on Internet advertising and sales. The value of a web site is inherently related to the number of potential customers who come to the site for information and eventually purchase a product or execute a service. However, financial analysts are having difficulty in valuing e-businesses. The purpose of this paper is to conduct an evaluation of cunently used web metrics. We intend to consider the relationship between stock prices and web metrics in addition to traditional accounting information for a sample of 15 top Internet companies. Specifically, we developed various regression models with the following four variables: unique visitors, revenues, gross margin and sales & marketing expenses. Our results support the hypothesis that web metrics do as good a job at explaining Internet stock prices as traditional accounting measures do. It appears that traditional accounting measures do not do an adequate job of explaining Internet stock prices. In sum, the predictive power of the web-based metric "unique visitors" appears to be a substantive and significant predictor of stock pnce.</p> |
Description: | <p>20 leaves. ; Includes bibliographical references (leaves 19-20). ;</p> |
URI: | http://hdl.handle.net/11375/5360 |
Identifier: | mint/10 1009 4943590 |
Appears in Collections: | MINT (Management of Innovation and New Technology) Research Centre Working Paper Series |
Files in This Item:
File | Size | Format | |
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fulltext.pdf | 1.01 MB | Adobe PDF | View/Open |
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