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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: Sundaresh Ramnath
Publisher: Now Publishers Inc
ISBN: 1601981627
Category : Business & Economics
Languages : en
Pages : 125
Get Book Here
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: Stephen M. Black
Publisher:
ISBN:
Category :
Languages : en
Pages : 304
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Book Description
Author: Logann Yeh
Publisher:
ISBN:
Category : Stock price forecasting
Languages : en
Pages : 92
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Book Description
Author: Russell Theodore Gingras
Publisher:
ISBN:
Category : Business forecasting
Languages : en
Pages : 384
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Book Description
Author: Brian R. Bruce
Publisher: Irwin Professional Publishing
ISBN:
Category : Business & Economics
Languages : en
Pages : 398
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Book Description
Author: Richard D. F. Harris
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Existing accounting-based forecasting models of earnings either do not fully consider information that is contained in stock prices or use an ad hoc specification that is not based on rigorous valuation theory. In this paper, we develop an earnings forecasting model built on the theoretical linkages between future earnings and stock prices as well as a number of accounting fundamental variables. We find that our model-based forecasts of earnings are in general less biased and more accurate than both existing model-based forecasts and analysts' consensus forecasts, at both shorter and longer horizons. We also show that the accuracy of both model-based forecasts and financial analysts' forecasts depend on firm-specific characteristics such as firm size and industry membership.
Author: Cheng Few Lee
Publisher: World Scientific
ISBN: 9811202400
Category : Business & Economics
Languages : en
Pages : 5053
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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: Robert H. Shumway
Publisher:
ISBN: 9781475732627
Category :
Languages : en
Pages : 568
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Book Description
Author: Gerald J. Lobo
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
This study investigates the relationship between the dispersion of analysts' earnings forecasts and stock price variability around quarterly earnings announcements. Consistent with theoretical predictions, the empirical analysis shows that stock price variability at the time of earnings announcements is positively related to the degree of analysts' earnings forecast dispersion. The analysis also demonstrates that stock price variability is significantly greater from two days before to two days after the earnings announcement for firms ranked in the bottom third on the basis of analysts' forecast dispersion, whereas it is significantly greater from eight days prior to five days following the earnings announcement for firms in the top third. These results suggest that there is information about the earnings announcement that becomes available to at least a subset of investors prior to the earnings release. The increased level of price variability for five days following the earnings announcement suggests that market participants take different amounts of time to process the information conveyed by the earnings announcement.
Author: Sati P. Bandyopadhyay
Publisher:
ISBN:
Category :
Languages : en
Pages : 17
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Book Description
Little attention has been paid to a principal decision context in which analysts' earnings forecasts are prepared, namely, as an input to their recommendations. We use two data sets, Value Line, USA, and Research Evaluation Service, Canada, and examine the importance of analysts' earnings forecasts for their stock price forecasts via three hypotheses: (1) analysts' earnings forecasts are important for their stock price forecasts; (2) analysts' long-term earnings forecasts are more important than their short-term earnings forecasts for their predictions of stock prices over a particular stock price forecast horizon; (3) the importance of analysts' earnings forecasts for their stock price forecasts rises as the joint earnings and stock price forecast horizon increases. We show that: (1) when the earnings forecast horizon is the next fiscal year, forecasted earnings explain only 30% of the variation in forecasted price; (2) the importance of forecasted earnings for forecasted price rises as the earnings forecast horizon increases; (3) in the long run, (i.e. three to five years hence), forecasted earnings explain about 60% of the variation in forecasted price. Decision usefulness is an ex ante concept, but tests regarding the usefulness of earnings for stock price generally have used actual (not expectational) data. Our evidence suggests that earnings expectations are decision useful, where the decision context is sell-side analysts' stock price forecasts. Our results are potentially important to users of sell-side analyst research reports. When a stock recommendation is accompanied only by short-run earnings forecasts, investors need to closely examine estimates of non-earnings variables to assess the quality of stock recommendations. In contrast, when stock recommendations are accompanied by both short-run and long-run earnings forecasts, investors need to examine estimates of non-earnings information variables less closely.
