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Author: Lawrence D. Brown Publisher: ISBN: Category : Languages : en Pages : 38
Book Description
We examine interactions between analyst earnings forecasts and management earnings forecasts by investigating: (1) managers' comparative efficiency relative to analysts at incorporating past earnings changes, accruals, stock returns and analyst-based earnings surprises into their earnings forecasts; (2) extent to which analyst inefficiencies in incorporating these four pieces of publicly available information into their earnings forecasts prompt managers to issue earnings forecasts; and (3) role of these four pieces of information at improving analyst forecasts after they have observed management forecasts. We show that: (1) unlike analysts, managers do efficiently incorporate information from past returns into their earnings forecasts; (2) analysts' failure to incorporate past returns information into earnings forecasts is the primary trigger for managers to issue their own earnings forecasts; and (3) after management forecasts, analyst forecasts improve most significantly with respect to incorporating past returns information.
Author: Lawrence D. Brown Publisher: ISBN: Category : Languages : en Pages : 38
Book Description
We examine interactions between analyst earnings forecasts and management earnings forecasts by investigating: (1) managers' comparative efficiency relative to analysts at incorporating past earnings changes, accruals, stock returns and analyst-based earnings surprises into their earnings forecasts; (2) extent to which analyst inefficiencies in incorporating these four pieces of publicly available information into their earnings forecasts prompt managers to issue earnings forecasts; and (3) role of these four pieces of information at improving analyst forecasts after they have observed management forecasts. We show that: (1) unlike analysts, managers do efficiently incorporate information from past returns into their earnings forecasts; (2) analysts' failure to incorporate past returns information into earnings forecasts is the primary trigger for managers to issue their own earnings forecasts; and (3) after management forecasts, analyst forecasts improve most significantly with respect to incorporating past returns information.
Author: Cheng Few Lee Publisher: World Scientific ISBN: 9811202400 Category : Business & Economics Languages : en Pages : 5053
Book Description
This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.
Author: Mark Bagnoli Publisher: ISBN: Category : Languages : en Pages : 58
Book Description
We ask whether the history of interactions between a firm and its analysts affects management's quarterly earnings forecast decision and analysts' subsequent earnings estimate revisions. We show that the history of their interactions not only reflects their individual incentives but is also used to form expectations about current decisions. Specifically, guidance is more likely to be pessimistically biased if management has a history of offering pessimistic forecasts and if analysts have tended to respond passively (i.e., by mimicking guidance or revising in the direction indicated by management). Individual analysts are more likely to respond passively to management's current forecast if they have historically responded in such a manner or if management has tended to offer unbiased or accurate guidance. Analysts with superior earnings forecasting track records are less likely to respond passively to guidance that is pessimistically biased. Collectively, our results indicate that downward bias in quarterly guidance and information production by analysts depend on what management and analysts have learned about each other over time as reflected in their forecasting histories.
Author: D. Eric Hirst Publisher: ISBN: Category : Languages : en Pages : 50
Book Description
In this paper, we provide a framework in which to view management earnings forecasts. Specifically, we categorize earnings forecasts as having three components - antecedents, characteristics, and consequences that roughly correspond to the timeline associated with an earnings forecast. By evaluating management earnings forecast research within the context of this framework, we render three conclusions. First, forecast characteristics appear to be the least well-understood component of earnings forecasts - both in terms of theory and empirical research - even though it is the component over which managers have the most control. Second, much of the prior research focuses on how one forecast antecedent or characteristic influences forecast consequences and does not study potential interactions among the three components. Third, much of the prior research ignores the iterative nature of management earnings forecasts - that is, forecast consequences of the current period influence antecedents and chosen characteristics in subsequent periods. Implications for researchers as well as educators, managers, investors, and regulators are provided.
Author: Sundaresh Ramnath Publisher: Now Publishers Inc ISBN: 1601981627 Category : Business & Economics Languages : en Pages : 125
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: Steven Lustgarten Publisher: ISBN: Category : Languages : en Pages :
Book Description
In this study we test whether financial analysts' use their earnings forecasts to make stock recommendations. We hypothesize that if analysts use earnings forecasts as a basis for stock recommendations, the likelihood of a buy (sell) recommendation ought to increase (decrease) when the analyst's earnings forecast becomes more optimistic (pessimistic) relative to the market's expectation. The data supports this hypothesis. We also test the extent to which analysts' stock recommendations are based on public and/or on private earnings information. Private information is measured as the difference between the analysts own earnings forecast and the consensus forecasts of other analysts. Public information is measured as the difference between the consensus forecast and the random walk forecast. Our data show that stock recommendations are related to both private and public earnings information, private information is more important. We also find that the relationship between recommendations and forecasts is stronger where earnings are more value relevant. Factors such as higher earnings persistence and growth opportunities, lower market risk and larger firm size make stock recommendations more responsive to earnings forecasts. Stock recommendations are related to forecasted earnings surprises even when the forecast revision is held constant.
Author: Shankar Venkataraman Publisher: ISBN: Category : Languages : en Pages :
Book Description
In this paper, we provide a framework in which to view management earnings forecasts. Specifically, we categorize earnings forecasts as having three components - antecedents, characteristics, and consequences - that roughly correspond to the timeline associated with an earnings forecast. By evaluating management earnings forecast research within the context of this framework, we render three conclusions. First, forecast characteristics appear to be the least well-understood component of earnings forecasts - both in terms of theory and empirical research - even though it is the component over which managers have the most control. Second, much of the prior research focuses on how one forecast antecedent or characteristic influences forecast consequences and does not study potential interactions among the three components. Third, much of the prior research ignores the iterative nature of management earnings forecasts - that is, forecast consequences of the current period influence antecedents and chosen characteristics in subsequent periods. Implications for researchers as well as educators, managers, investors, and regulators are provided.
Author: Lawrence D. Brown
Author: Lawrence D. Brown
Author: Cheng Few Lee
Author: Mark Bagnoli
Author: Christoph Emanuel Jorns
Author: D. Eric Hirst
Author: Sundaresh Ramnath
Author: Steven Lustgarten
Author: Shankar Venkataraman
Author: Wenjuan Xie
Author: Paul A. Janell