We show that analysts from sell-side firms generally recommend "glamour" (i.e., positive momentum, high growth, high volume, and relatively expensive) stocks. Naïve adherence to these recommendations can be costly, because the level of the consensus recommendation adds value only among stocks with favorable quantitative characteristics (i.e., value stocks and positive momentum stocks). In fact, among stocks with unfavorable quantitative characteristics, higher consensus recommendations are associated with worse subsequent returns. In contrast, we find that the quarterly change in consensus recommendations is a robust return predictor that appears to contain information orthogonal to a large range of other predictive variables.FINANCIAL RESEARCHERS AND PRACTITIONERS have long been interested in understanding how the activities of financial analysts affect capital market efficiency. Currently in the United States, over 3,000 analysts work for more than 350 sellside investment firms. 1 These analysts produce corporate earnings forecasts, write reports on individual companies, provide industry and sector analyses, and issue stock recommendations. Most prior studies have concluded that the information they produce promotes market efficiency by helping investors to more accurately value companies. 2The Journal of Finance about the intrinsic stock values relative to their current market prices, and finally rate the investment potential of each stock. As Elton, Gruber, and Grossman (1986, p. 699) observe, their stock recommendations represent "one of the few cases in evaluating information content where the forecaster is recommending a clear and unequivocal course of action rather than producing an estimate of a number, the interpretation of which is up to the user." In short, these recommendations offer a unique opportunity to study analyst judgment and preferences across large samples of stocks.Our study investigates the source of the investment value provided by analyst stock recommendations and changes in recommendations. One possible source of this value is the ability of analysts to collect and process firm-specific information useful in identifying undervalued or overvalued stocks. Alternatively, it is possible that analyst recommendations derive their value by tilting toward stocks with particular characteristics that predict future returns. We assess the contribution of these sources of potential value.We also assess the extent to which sell-side analysts make full use of available information signals in formulating stock recommendations. We find that analysts do not fully take into account the ability of various stock characteristics to predict returns. Moreover, our evidence shows that the direction of the bias in analyst recommendations is in line with economic incentives faced by sell-side brokerage firms.We expect this research to be of interest to both financial academics and practitioners. From an academic perspective, the study contributes to a better understanding of how analysts evaluate stocks, and ...

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This research examines how investment experience and financial literacy impact investment‐related judgments. Financial literacy refers to a person's knowledge of fundamental financial concepts. I begin by documenting investors' demographic characteristics and financial literacy using a relatively large sample of participants (n > 2,000) recruited from Amazon's Mechanical Turk under different categories of investment experience, which I benchmark against national samples of financial capability skills in the United States. I then replicate a sample of three accounting research experiments, varying the type and depth of the underlying accounting issue. Across the three experiments, the data show two main results: First, investment experience strengthens the influence of financial accounting disclosures on participants' investment‐related judgments. Second, financial literacy further strengthens the influence of financial accounting disclosures on investors' (but not noninvestors') judgments. Collectively, these findings suggest that investment experience and financial literacy can help to identify individuals who are more likely to be able and willing to study financial reporting information with reasonable diligence as they form their investment‐related judgments.

Prior research demonstrates that forecast optimism is, in part, a consequence of analysts' cognitive reactions to the scenarios managers use to communicate future plans. In two experiments, we examine whether counter-explanation (explaining why managers' plans could fail) reduces scenario-induced optimism. We find that when compared to analysts not asked to generate counter-explanations, analysts who complete the relatively easy task of generating few counter-explanations make less optimistic forecasts, but analysts who complete the relatively difficult task of generating many counter-explanations do not. Results demonstrate the usefulness of a cognitive, theory-based mechanism for reducing forecast optimism and suggest a boundary condition for the use of that mechanism.