Analysts' Forecasts as Proxies for Investor Beliefs in Empirical Research PDF Download
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Author: Jeffery S. Abarbanell
Publisher:
ISBN:
Category : Investment analysis
Languages : en
Pages : 56
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Author: Jeffery S. Abarbanell
Publisher:
ISBN:
Category : Investment analysis
Languages : en
Pages : 56
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Author: Shuping Chen
Publisher:
ISBN:
Category :
Languages : en
Pages :
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This paper investigates the conclusion in Diether, Malloy, and Scherbina (2002) that dispersion in analysts' forecasts proxies for differences in investor beliefs, and that prices reflect the beliefs of optimistic investors when dispersion is high. If this is the case, we expect to find higher earnings response coefficients (ERCs), related to negative earnings surprises, for high versus low dispersion firms. This follows because the negative earnings surprises are less consistent with the beliefs of optimists. However, we find smaller ERCs, which calls into question the optimism argument in DMS. Further, we find that the relatively low future returns earned by high forecast dispersion firms, documented in DMS, are explained by the well known post-earnings-announcement drift phenomena. Specifically, after sorting observations based on prior period standardized unexpected earnings (SUEs), which are associated with drift, the difference between the future returns of high versus low dispersion firms is not statistically significant.
Author: Davit Adut
Publisher:
ISBN:
Category :
Languages : en
Pages :
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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.
Author: Patricia C. O'brien
Publisher: Forgotten Books
ISBN: 9781334538919
Category : Mathematics
Languages : en
Pages : 76
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Excerpt from Analysts' Forecasts as Earnings Expectations The use of predictions from univariate time-series models of earnings as earnings expectations has been more common than the use of analysts' forecasts, in part because of data availability However, several studies (brown and Rozeff Collins and Hopwood Fried and Givoly demonstrate that analysts are more accurate than univariate models, presumably because they can incorporate a broader information set than can a univariate model. Fried and Givoly also find that analysts' forecast errors are more closely associated with excess stock returns than are those of univariate models. An additional limitation of time - series models is their substantial data requirements, which impart a sample selection bias to the research, toward longer-lived and larger firms. Since analysts forecasts require no parameter estimation, sample selection bias is less severe. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.
Author: Youfei Xiao
Publisher:
ISBN:
Category :
Languages : en
Pages :
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This dissertation is comprised of two studies on analyst forecasts. The first study provides empirical evidence about the objective function underlying analysts' choice of forecasts. Assumptions about sell-side analysts' objective function are critical to empirical researchers' understanding of their incentives and resulting behavior. In contrast to approaches used in previous papers which rely exclusively on statistical properties of forecasts, I compare theoretical models with alternate objective functions based on their ability to explain observed forecasts. A linear loss objective function which incorporates the effect future analysts' actions on analysts' deviation from peer forecasts is best rationalized by the data. I find that assumptions about the objective function have a substantial impact on the conclusions from empirical tests about analysts' incentives and behavior. The second study provides empirical estimates of uncertainty and disagreement about future earnings that underly analyst forecast dispersion. A parsimonious model which assumes that analysts' payoffs are jointly determined by forecast error and deviation from consensus reproduces many of the descriptive facts observed about forecast dispersion in the data. The strategic behavior that arises from the model distorts both the levels of forecast dispersion and the sensitivity of the measure with respect to cross-sectional variation in uncertainty. The estimated parameters perform better at predicting forecast dispersion out-of-sample than approaches based solely on regressions that use firm characteristics. Counterfactual simulations indicate that analysts' strategic incentives, together with the sequential forecast setting, plays a first-order role in determining forecast dispersion relative to the firm's information environment. The model-implied estimates of earnings uncertainty exhibit a substantially less negative association with future returns relative to the association generated by forecast dispersion. This finding partially reconciles the findings from previous studies with theories about the asset pricing implications of uncertainty and disagreement.
Author: Hakan Saraoglu
Publisher:
ISBN:
Category : Business forecasting
Languages : en
Pages : 318
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Author: Sundaresh Ramnath
Publisher: Now Publishers Inc
ISBN: 1601981627
Category : Business & Economics
Languages : en
Pages : 125
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Book Description
Financial Analysts' Forecasts and Stock Recommendations reviews research related to the role of financial analysts in the allocation of resources in capital markets. The authors provide an organized look at the literature, with particular attention to important questions that remain open for further research. They focus research related to analysts' decision processes and the usefulness of their forecasts and stock recommendations. Some of the major surveys were published in the early 1990's and since then no less than 250 papers related to financial analysts have appeared in the nine major research journals that we used to launch our review of the literature. The research has evolved from descriptions of the statistical properties of analysts' forecasts to investigations of the incentives and decision processes that give rise to those properties. However, in spite of this broader focus, much of analysts' decision processes and the market's mechanism of drawing a useful consensus from the combination of individual analysts' decisions remain hidden in a black box. What do we know about the relevant valuation metrics and the mechanism by which analysts and investors translate forecasts into present equity values? What do we know about the heuristics relied upon by analysts and the market and the appropriateness of their use? Financial Analysts' Forecasts and Stock Recommendations examines these and other questions and concludes by highlighting area for future research.
Author: Paul A. Janell
Publisher:
ISBN:
Category : Economic forecasting
Languages : en
Pages : 354
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Author: Seung-Woog Kwag
Publisher:
ISBN:
Category :
Languages : en
Pages : 110
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Author: Jana Smith Raedy
Publisher:
ISBN:
Category :
Languages : en
Pages : 33
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This paper provides empirical evidence that underreaction in financial analysts' earnings forecasts increases with the forecast horizon, and the paper offers a rational economic explanation for this result. The empirical portion of the paper evaluates analysts' responses to earnings-surprise and other earnings-related information. Our empirical evidence suggests that analysts' earnings forecasts underreact to both types of information, and the underreaction increases with the forecast horizon. The paper also develops a theoretical model that explains this horizon-dependent analyst underreaction as a rational response to an asymmetric loss function. The model assumes that, for a given level of inaccuracy, analysts' reputations suffer more (less) when subsequent information causes a revision in investor expectations in the opposite (same) direction as the analyst's prior earnings forecast revision. Given this asymmetric loss function, underreaction increases with the risk of subsequent disconfirming information and with the disproportionate cost associated with revision reversal. Assuming that market frictions prevent prices from immediately unraveling these analyst underreaction tactics, investors buying (selling) stock based on analysts' positive (negative) earnings forecast revisions also benefit from analyst underreaction. Therefore, the asymmetric cost of forecast inaccuracy could arise from rational investor incentives consistent with a preference for analyst underreaction. Our incentives-based explanation for underreaction provides an alternative to psychology-based explanations and suggests avenues for further research.
