This dissertation utilizes the event study methodology from the modern theory of finance to examine corporate name changes (CNCs). Data sources include press releases and articles announcing CNCs compiled by Lexis Nexis, annual reports collected from the SEC File microfiche database compiled by Q-Data and the EDGAR database compiled online by Mergent, and the Center for Research on Stock Prices and COMPUSTAT compiled by Wharton Research Data Services. These data sources are used to answer three primary research questions. First, what is the effect of a CNC related to a change in corporate image, as opposed to a change in corporate entity (e.g., acquisition), on a firm’s stock price? Second, what is the effect of a major change versus a minor change to the corporate name during a CNC related to a change in corporate image? Third, what is the effect of a non-brand name altering CNC versus a brand name altering CNC on a firm’s stock price? This dissertation makes its primary contribution to the study of CNCs by finding that CNCs related to a change in corporate image will have a positive impact on stock price whereas CNCs related to a change in corporate entity will not. Moreover, it finds that major changes to the corporate name during CNCs related to a change in corporate image will have a positive impact on a firm’s stock price whereas minor changes to the corporate name during CNCs related to a change in corporate image will not. Finally, it is the first study to examine the effect of CNCs on firms’ brand names and finds that non-brand name altering CNCs related to a change in corporate image will have a positive impact on a firm’s stock price whereas brand name altering CNCs related to a change in corporate image will not.
| Identifer | oai:union.ndltd.org:TEXASAandM/oai:repository.tamu.edu:1969.1/ETD-TAMU-1830 |
| Date | 02 June 2009 |
| Creators | DeFanti, Mark P. |
| Contributors | Busch, Paul S., Berry, Leonard L., Sorescu, Alina R., Woodman, Richard W. |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | thesis, text |
| Format | electronic, application/pdf, born digital |
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