Program and Proceedings

Program and Proceedings
Title Program and Proceedings PDF eBook
Author American Accounting Association
Publisher
Pages 388
Release 2007
Genre Accounting
ISBN

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Soft Information in Earnings Announcements

Soft Information in Earnings Announcements
Title Soft Information in Earnings Announcements PDF eBook
Author Elizabeth Demers
Publisher
Pages 66
Release 2008
Genre Corporations
ISBN

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This paper examines whether the "soft" information contained in the text of management's quarterly earnings press releases is incrementally informative over the company's reported "hard" earnings news. We use Diction, a textual-analysis program, to extract various dimensions of managerial net optimism from more than 20,000 corporate earnings announcements over the period 1998 to 2006 and document that unanticipated net optimism in managers' language affects announcement period abnormal returns and predicts post-earnings announcement drift. We find that it takes longer for the market to understand the implications of soft information than those of hard information. We also find that the market response varies by firm size, turnover, media and analyst coverage, and the extent to which the standard accounting model captures the underlying economics of the firm. We also show that the second moment of soft information, the level of certainty in the text, is an important determinant of contemporaneous idiosyncratic volatility, and it predicts future idiosyncratic volatility.

Earnings Management

Earnings Management
Title Earnings Management PDF eBook
Author Joshua Ronen
Publisher Springer Science & Business Media
Pages 587
Release 2008-08-06
Genre Business & Economics
ISBN 0387257713

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This book is a study of earnings management, aimed at scholars and professionals in accounting, finance, economics, and law. The authors address research questions including: Why are earnings so important that firms feel compelled to manipulate them? What set of circumstances will induce earnings management? How will the interaction among management, boards of directors, investors, employees, suppliers, customers and regulators affect earnings management? How to design empirical research addressing earnings management? What are the limitations and strengths of current empirical models?

Wall Street Research

Wall Street Research
Title Wall Street Research PDF eBook
Author Boris Groysberg
Publisher Stanford University Press
Pages 200
Release 2013-08-07
Genre Business & Economics
ISBN 0804787123

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Wall Street Research: Past, Present, and Future provides a timely account of the dramatic evolution of Wall Street research, examining its rise, fall, and reemergence. Despite regulatory, technological, and global forces that have transformed equity research in the last ten years, the industry has proven to be remarkably resilient and consistent. Boris Groysberg and Paul M. Healy get to the heart of Wall Street research—the analysts engaged in the process—and demonstrate how the analysts' roles have evolved, what drives their performance today, and how they stack up against their buy-side counterparts. The book unpacks key trends and describes how different firms have coped with shifting pressures. It concludes with an assessment of where equity research is headed in emerging markets, drawing conclusions about this often overlooked corner of Wall Street and the industry's future challenges.

Advances in Quantitative Analysis of Finance and Accounting (New Series) Vol.12

Advances in Quantitative Analysis of Finance and Accounting (New Series) Vol.12
Title Advances in Quantitative Analysis of Finance and Accounting (New Series) Vol.12 PDF eBook
Author Cheng F. Lee
Publisher Center for PBBEFR & Airiti Press
Pages
Release 2014-01-01
Genre Business & Economics
ISBN 9866286681

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Advances in Quantitative Analysis of Finance and Accounting (New Series) is an annual publication designed to disseminate developments in the quantitative analysis of finance and accounting. The publication is a forum for statistical and quantitative analyses of issues in finance and accounting as well as applications of quantitative methods to problems in financial management, financial accounting, and business management. The objective is to promote interaction between academic research in finance and accounting and applied research in the financial community and the accounting profession.

Handbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes)

Handbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes)
Title Handbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes) PDF eBook
Author Cheng Few Lee
Publisher World Scientific
Pages 5053
Release 2020-07-30
Genre Business & Economics
ISBN 9811202400

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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.

Dissertation Abstracts International

Dissertation Abstracts International
Title Dissertation Abstracts International PDF eBook
Author
Publisher
Pages 634
Release 2009
Genre Dissertations, Academic
ISBN

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