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Dispersion in analysts' forecasts: does it make a difference?

Financial analysts are an important group of information intermediaries in the capital markets. Their reports, including both earnings forecasts and stock recommendations, are widely transmitted and have a significant impact on stock prices (Womack 1996; Lys and Sohn 1990, among others). Empirical accounting research frequently relies on analysts' forecasts to construct proxies for variables of interest. For example, the error in mean forecast is used as a proxy for earnings surprise (e.g., Brown et al.1987; Wiedman 1996; Bamber et al.1997). More recent papers provide evidence that the mean consensus forecast is used as a benchmark for evaluating firm performance. (Degeorge et al. 1999; Kasznik and McNichols 2002; Lopez and Rees 2002).

Another stream of research uses the forecast dispersion as a proxy for the uncertainty or the degree of consensus among analysts and focuses on the information properties of analysts (e.g., Daley et al. 1988; Ziebart 1990; Imhoff and Lobo 1992; Lang and Lundholm 1996; Barron and Stuerke 1998; Barron et al. 1998). In this paper I combine the two streams of research, and investigate how lack of consensus changes the information environment of analysts and whether the markets perceive this change. More specifically, I investigate the amount of private information in a divergent earnings estimate (i.e. one that is above or below the consensus), whether the markets react to it at either the time of the forecast release, at the realization of actual earnings, and whether Regulation Fair Disclosure has changed the information environment differently for high and low dispersion firms.

Identiferoai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/161
Date30 September 2004
CreatorsAdut, Davit
ContributorsLoudder, Martha L.
PublisherTexas A&M University
Source SetsTexas A and M University
Languageen_US
Detected LanguageEnglish
TypeElectronic Dissertation, text
Format853240 bytes, 111930 bytes, electronic, application/pdf, text/plain, born digital

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