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The Geography of Equity Analysis



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    • Christopher J. Malloy is from the London Business School. This paper is a revised version of my Ph.D. dissertation at the University of Chicago. I thank my advisors Gene Fama, Owen Lamont, Toby Moskowitz, Lubos Pastor, and Raghu Rajan, as well as Nick Barberis, Karl Diether, Gilles Hilary, Rick Green (the editor), Steve Kaplan, Richard Leftwich, Lior Menzly; an anonymous referee; and seminar participants at London Business School, Ohio State, University of Chicago, University of Virginia, Yale, and the AEA Annual Meeting for helpful comments and suggestions. I also gratefully acknowledge the contribution of Thomson Financial for providing earnings per share forecast data, available through I/B/E/S. These data have been provided as part of a broad academic program to encourage earnings expectations research. All remaining errors are my own.


I provide evidence that geographically proximate analysts are more accurate than other analysts. Stock returns immediately surrounding forecast revisions suggest that local analysts impact prices more than other analysts. These effects are strongest for firms located in small cities and remote areas. Collectively these results suggest that geographically proximate analysts possess an information advantage over other analysts, and that this advantage translates into better performance. The well-documented underwriter affiliation bias in stock recommendations is concentrated among distant affiliated analysts; recommendations by local affiliated analysts are unbiased. This finding reveals a geographic component to the agency problems in the industry.