An Information Interpretation of Financial Analyst Superiority in Forecasting Earnings

20 Pages Posted: 22 May 2008

See all articles by Lawrence D. Brown

Lawrence D. Brown

Temple University - Department of Accounting

Gordon D. Richardson

University of Toronto - Rotman School of Management

Abstract

This paper develops and tests an information-based model for conditions under which analysts earnings forecasts are likely to be more accurate than forecasts of time-series models. Three information variables are considered, namely the dimensionality of the information set, the precision of the information items, and the correlation amongst the information items. The respective proxy variables for the information variables are firm size, extent of agreement amongst analysts, and the number of lines of business the firm operates in. Evidence is provided that analysts are likely to be more accurate than time series models for larger firms and for firms whereby analysts have more homogeneous earnings forecasts.

Suggested Citation

Brown, Lawrence D. and Richardson, Gordon D., An Information Interpretation of Financial Analyst Superiority in Forecasting Earnings. Journal of Accounting Research, Vol. 25, No. 1, Spring 1987. Available at SSRN: https://ssrn.com/abstract=1121408

Lawrence D. Brown (Contact Author)

Temple University - Department of Accounting ( email )

Philadelphia, PA 19122
United States

Gordon D. Richardson

University of Toronto - Rotman School of Management ( email )

105 St. George Street
Toronto, Ontario M5S 3E6 M5S1S4
Canada
416-946-8601 (Phone)
416-971-3048 (Fax)

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