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Author: Lawrence D. Brown
Publisher:
ISBN:
Category :
Languages : en
Pages : 17
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Book Description
The extant literature has concluded that stock prices do not fully reflect the implications of current earnings for future earnings. This evidence is based on random samples of firms, whose quarterly earnings are assumed to be generated by the same, relatively complex, Brown-Rozeff (1979, BR hereafter) process. It is conceivable that model complexity is the source of the market's failure to fully reflect the implications of current earnings for future earnings. The purpose of this study is to determine whether stock prices fully reflect the implications of current earnings for future earnings for a subset of firms whose quarterly earnings generating process is much simpler than the BR model. For the entire sample of AR1 firms, we find that stock prices do not fully reflect the implications of current quarterly earnings for future quarterly earnings. They erroneously act as if the error of the AR1 model at lag four has negative valuation implications. When we segment the sample by several proxy variables for firms' information environments (i.e., firm size, number of institutional shareholders, and the existence of security analyst following), we find that the failure of stock prices to fully reflect the implications of current quarterly earnings for future quarterly earnings pertains only to firms with less predisclosure information. When we examine the relation between current earnings surprise and contemporaneous and future CARs, we obtain additional insights into what stock prices do not understand about firms with less predisclosure information. For firms with less predisclosure information, the failure of stock prices to fully reflect the implications of current quarterly earnings for future quarterly earnings pertains to large positive surprises, but not to large negative ones.
Author: Lawrence D. Brown
Publisher:
ISBN:
Category :
Languages : en
Pages : 17
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Book Description
The extant literature has concluded that stock prices do not fully reflect the implications of current earnings for future earnings. This evidence is based on random samples of firms, whose quarterly earnings are assumed to be generated by the same, relatively complex, Brown-Rozeff (1979, BR hereafter) process. It is conceivable that model complexity is the source of the market's failure to fully reflect the implications of current earnings for future earnings. The purpose of this study is to determine whether stock prices fully reflect the implications of current earnings for future earnings for a subset of firms whose quarterly earnings generating process is much simpler than the BR model. For the entire sample of AR1 firms, we find that stock prices do not fully reflect the implications of current quarterly earnings for future quarterly earnings. They erroneously act as if the error of the AR1 model at lag four has negative valuation implications. When we segment the sample by several proxy variables for firms' information environments (i.e., firm size, number of institutional shareholders, and the existence of security analyst following), we find that the failure of stock prices to fully reflect the implications of current quarterly earnings for future quarterly earnings pertains only to firms with less predisclosure information. When we examine the relation between current earnings surprise and contemporaneous and future CARs, we obtain additional insights into what stock prices do not understand about firms with less predisclosure information. For firms with less predisclosure information, the failure of stock prices to fully reflect the implications of current quarterly earnings for future quarterly earnings pertains to large positive surprises, but not to large negative ones.
Author: Michael Calegari
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Analysts have been found to underweight the innovation in most recent quarter earnings when forecasting next quarter earnings, and these expectations have been posited as an explanation for post-earnings announcement drift. This study uses an experimental asset market to examine whether similar errors are made by student subjects in forecasting quarterly earnings. We examine two aspects of behavior: (1) Do subjects underestimate the autocorrelation in quarterly earnings when forming earnings expectations? and (2) Are asset prices consistent with subjects underestimating the autocorrelation in quarterly earnings? We observe errors in forecasts by subjects which underweight extreme innovations in the most recent quarter earnings by approximately forty percent. The prices in the experimental markets also fail to reflect fully the most recent innovation in quarterly earnings. We are able to predict the sign of the mispricing in 74 percent of the 135 markets from the mean initial earnings predictions of the subjects. These forecast errors observed in this study are consistent with forecast errors observed for analysts, and this consistency suggests that errors in analysts' forecasts may be at least partially attributable to the use of judgmental heuristics.
Author: Richard G. Sloan
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
This paper investigates whether stock prices reflect information about future earnings contained in the accrual and cash flow components of current earnings. The extent to which current earnings performance persists into the future is shown to depend on the relative magnitudes of the cash and accrual components of current earnings. However, stock prices are found to act as if investors quot;fixatequot; on earnings, failing to fully reflect information in the accrual and cash flow components of current earnings until it impacts future earnings.
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: Philip M J Reckers
Publisher: Elsevier
ISBN: 0080463215
Category : Business & Economics
Languages : en
Pages : 287
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Book Description
The twenty-second volume of Advances in Accounting continues to provide an important forum for discourse among and between academic and practicing accountants on issues of significance to the future of the discipline. Emphasis continues to be placed on original commentary, critical analysis and creative research – research that promises to substantively advance our understanding of financial markets, behavioral phenomenon and regulatory policy. Technology and aggressive global competition have propelled tremendous changes over the two decades since AIA was founded. A wide array of unsolved questions continues to plague a profession under fire in the aftermath of one financial debacle after another and grabbling with the advent of international accounting standards. This volume of Advances in Accounting not surprisingly includes several articles reflective on auditor independence, auditor tenure, auditor rotation and non-audit service fees. This volume also looks at challenges facing the academic community with respect to pressures placed on faculty to publish; a data driven commentary is provided by the in-coming editor of the European Accounting Review. Other papers examine the use of financial data to estimate risk premiums, and measure the operating efficiency of firms; and re-examine market reaction to quarterly earnings. AIA continues its commitment to the global arena by publishing several papers with an international perspective. As never before the accounting profession is seeking ways to reinvent itself and recapture relevance and credibility. AIA likewise continues to champion forward thinking research. *Addresses the role of the auditor *Investigates how financial data is represented, used, and received *Scope of content is international
Author: Jiangfan Wen
Publisher:
ISBN:
Category : Cash flow
Languages : en
Pages : 188
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Book Description
Author: Phillip Cagan
Publisher:
ISBN:
Category : Corporate profits
Languages : en
Pages : 52
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Book Description
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 898
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Book Description
Author: Pieter Johannes Heyns
Publisher:
ISBN:
Category : Cash flow
Languages : en
Pages : 130
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Book Description
Author: Sarah E. Bonner
Publisher: Prentice Hall
ISBN:
Category : Business & Economics
Languages : en
Pages : 488
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Book Description
This unique first edition is the only book on the market that delivers a contemporary synthesis of both psychology and accounting literature related to judgment and decision making. Judgment and Decision Making in Accounting is structured around an innovative framework that provides a unique way of thinking about JDM projects and organizing JDM research. Developed based on many years of teaching and research on accounting JDM, this unique framework succinctly describes the key issues in accounting JDM research, enabling readers to more quickly assimilate the vast material related to those issues. The framework also provides a basis to help readers evaluate their own current JDM research ideas, as well as generate further research questions.
