“…To this end, researchers have long studied the relative accuracy of analysts' earnings forecasts in hopes of acquiring greater insight into these subjects. Such research work has been reported by Richards (1976), Brown and Rozeff (1980), O'Brien (1987O'Brien ( , 1990, Butler and Lang (1991), Stickel (1992), Sinha et al (1997), and other authors whose empirical findings have been summarized in Ramnath et al (2008, Sect. 3.2).…”
The main purpose of this paper is to analyze the time patterns of individual analysts' relative accuracy ranking in earnings forecasts using a Markov chain model. Two levels of stochastic persistence are found in analysts' relative accuracy over time. Factors underlying analysts' performance persistence are identified and they include analyst's length of experience, workload, and the size and growth rate of firms followed by the analyst. The strength and the composition of these factors are found to vary markedly in different industries. The findings support the general notion that analysts are heterogeneous in their accuracy in earnings forecasts and that their superior/inferior performance tends to persist over time. An analysis based on a refined measure of analysts' forecast accuracy ranking that strips off firm-specific factors further enhances the empirical validity of the findings. These findings provide a concrete basis for researchers to further explore why and how analysts perform differently in the competitive market of investment information services.
“…To this end, researchers have long studied the relative accuracy of analysts' earnings forecasts in hopes of acquiring greater insight into these subjects. Such research work has been reported by Richards (1976), Brown and Rozeff (1980), O'Brien (1987O'Brien ( , 1990, Butler and Lang (1991), Stickel (1992), Sinha et al (1997), and other authors whose empirical findings have been summarized in Ramnath et al (2008, Sect. 3.2).…”
The main purpose of this paper is to analyze the time patterns of individual analysts' relative accuracy ranking in earnings forecasts using a Markov chain model. Two levels of stochastic persistence are found in analysts' relative accuracy over time. Factors underlying analysts' performance persistence are identified and they include analyst's length of experience, workload, and the size and growth rate of firms followed by the analyst. The strength and the composition of these factors are found to vary markedly in different industries. The findings support the general notion that analysts are heterogeneous in their accuracy in earnings forecasts and that their superior/inferior performance tends to persist over time. An analysis based on a refined measure of analysts' forecast accuracy ranking that strips off firm-specific factors further enhances the empirical validity of the findings. These findings provide a concrete basis for researchers to further explore why and how analysts perform differently in the competitive market of investment information services.
“…Richards (1976), Brown and Rozeff (1980), O'Brien (1987), Coggin and Hunter (1989), O'Brien (1990), Butler and Lang (1991), Sinha et al (1997), and Cooper et al (2001) investigate differences in the earnings forecast accuracy across analysts; Sinha et al (1997) is the closest in spirit to my paper. They find that superior earnings forecasters in one period tend to be superior in subsequent holdout periods, which suggests persistence in earnings forecast accuracy.…”
“…In preparing this second file it was soon apparent that brokers seem to reach a consensus when forecasting profits for a particular company at a given point in time, a phenomenon already observed in the United States (see, for example, Comiskey, 1975a, 1975b;Basi, Carey and Twark, 1976;and Richards, 1976). In fact.…”
Section: The Datamentioning
confidence: 95%
“…However, Dev and Webb (1972), Daily (1971) and Westwick (1972) employed A, -F,, and others have used (Fi -A,) -Ai (e.g. Copeland and Marioni, 1972;Basi, Carey and Twark, 1976;Richards, 1976;Brown and Rozeff, 1978).…”
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