Author: Joshua Ronen
Publisher: Springer Science & Business Media
ISBN: 0387257713
Category : Business & Economics
Languages : en
Pages : 587
Book Description
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?
Earnings Management
Author: Joshua Ronen
Publisher: Springer Science & Business Media
ISBN: 0387257713
Category : Business & Economics
Languages : en
Pages : 587
Book Description
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?
Publisher: Springer Science & Business Media
ISBN: 0387257713
Category : Business & Economics
Languages : en
Pages : 587
Book Description
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?
Introduction to Financial Forecasting in Investment Analysis
Author: John B. Guerard, Jr.
Publisher: Springer Science & Business Media
ISBN: 1461452392
Category : Business & Economics
Languages : en
Pages : 245
Book Description
Forecasting—the art and science of predicting future outcomes—has become a crucial skill in business and economic analysis. This volume introduces the reader to the tools, methods, and techniques of forecasting, specifically as they apply to financial and investing decisions. With an emphasis on "earnings per share" (eps), the author presents a data-oriented text on financial forecasting, understanding financial data, assessing firm financial strategies (such as share buybacks and R&D spending), creating efficient portfolios, and hedging stock portfolios with financial futures. The opening chapters explain how to understand economic fluctuations and how the stock market leads the general economic trend; introduce the concept of portfolio construction and how movements in the economy influence stock price movements; and introduce the reader to the forecasting process, including exponential smoothing and time series model estimations. Subsequent chapters examine the composite index of leading economic indicators (LEI); review financial statement analysis and mean-variance efficient portfolios; and assess the effectiveness of analysts’ earnings forecasts. Using data from such firms as Intel, General Electric, and Hitachi, Guerard demonstrates how forecasting tools can be applied to understand the business cycle, evaluate market risk, and demonstrate the impact of global stock selection modeling and portfolio construction.
Publisher: Springer Science & Business Media
ISBN: 1461452392
Category : Business & Economics
Languages : en
Pages : 245
Book Description
Forecasting—the art and science of predicting future outcomes—has become a crucial skill in business and economic analysis. This volume introduces the reader to the tools, methods, and techniques of forecasting, specifically as they apply to financial and investing decisions. With an emphasis on "earnings per share" (eps), the author presents a data-oriented text on financial forecasting, understanding financial data, assessing firm financial strategies (such as share buybacks and R&D spending), creating efficient portfolios, and hedging stock portfolios with financial futures. The opening chapters explain how to understand economic fluctuations and how the stock market leads the general economic trend; introduce the concept of portfolio construction and how movements in the economy influence stock price movements; and introduce the reader to the forecasting process, including exponential smoothing and time series model estimations. Subsequent chapters examine the composite index of leading economic indicators (LEI); review financial statement analysis and mean-variance efficient portfolios; and assess the effectiveness of analysts’ earnings forecasts. Using data from such firms as Intel, General Electric, and Hitachi, Guerard demonstrates how forecasting tools can be applied to understand the business cycle, evaluate market risk, and demonstrate the impact of global stock selection modeling and portfolio construction.
Earnings Management
Author: Joshua Ronen
Publisher: Springer Science & Business Media
ISBN: 0387257691
Category : Business & Economics
Languages : en
Pages : 587
Book Description
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?
Publisher: Springer Science & Business Media
ISBN: 0387257691
Category : Business & Economics
Languages : en
Pages : 587
Book Description
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?
The Statistical Theory of Linear Systems
Author: E. J. Hannan
Publisher: SIAM
ISBN: 1611972183
Category : Business & Economics
Languages : en
Pages : 418
Book Description
Originally published: New York: Wiley, c1988.
Publisher: SIAM
ISBN: 1611972183
Category : Business & Economics
Languages : en
Pages : 418
Book Description
Originally published: New York: Wiley, c1988.
Introduction to Earnings Management
Author: Malek El Diri
Publisher: Springer
ISBN: 3319626868
Category : Business & Economics
Languages : en
Pages : 120
Book Description
This book provides researchers and scholars with a comprehensive and up-to-date analysis of earnings management theory and literature. While it raises new questions for future research, the book can be also helpful to other parties who rely on financial reporting in making decisions like regulators, policy makers, shareholders, investors, and gatekeepers e.g., auditors and analysts. The book summarizes the existing literature and provides insight into new areas of research such as the differences between earnings management, fraud, earnings quality, impression management, and expectation management; the trade-off between earnings management activities; the special measures of earnings management; and the classification of earnings management motives based on a comprehensive theoretical framework.
Publisher: Springer
ISBN: 3319626868
Category : Business & Economics
Languages : en
Pages : 120
Book Description
This book provides researchers and scholars with a comprehensive and up-to-date analysis of earnings management theory and literature. While it raises new questions for future research, the book can be also helpful to other parties who rely on financial reporting in making decisions like regulators, policy makers, shareholders, investors, and gatekeepers e.g., auditors and analysts. The book summarizes the existing literature and provides insight into new areas of research such as the differences between earnings management, fraud, earnings quality, impression management, and expectation management; the trade-off between earnings management activities; the special measures of earnings management; and the classification of earnings management motives based on a comprehensive theoretical framework.
Financial Statement Analysis and Earnings Forecasting
Author: Steven J. Monahan
Publisher: Foundations and Trends (R) in Accounting
ISBN: 9781680834505
Category :
Languages : en
Pages : 124
Book Description
Financial Statement Analysis and Earnings Forecasting is the process of analyzing historical financial statement data for the purpose of developing forecasts of future earnings. This process is important because it is central to the valuation of companies and the securities they issue. After a short introduction, Section 2 delves into the question "Why earnings"? Focusing on dividend policy irrelevance, the author describes key analytical results that imply that expected earnings are the fundamental determinant of both equity and enterprise value. Section 3 examines the issues involved in selecting the earnings metric to forecast. Once an earnings metric has been chosen, the next question to ask is "How useful are historical accounting numbers for developing forecasts of that metric?" Sections 4 through 8 focus on this question. Section 4 discusses the general role of econometric modeling. Section 5 reviews time-series models. Section 6 examines the choices a researcher makes when using panel-data approaches and the author describes the advantages of these approaches. Section 7 reviews the role of accounting measurement in determining the usefulness of historical accounting numbers for developing forecasts of future earnings. Section 8 examines approaches for forecasting the higher moments of future earnings and section 9 provides a summary.
Publisher: Foundations and Trends (R) in Accounting
ISBN: 9781680834505
Category :
Languages : en
Pages : 124
Book Description
Financial Statement Analysis and Earnings Forecasting is the process of analyzing historical financial statement data for the purpose of developing forecasts of future earnings. This process is important because it is central to the valuation of companies and the securities they issue. After a short introduction, Section 2 delves into the question "Why earnings"? Focusing on dividend policy irrelevance, the author describes key analytical results that imply that expected earnings are the fundamental determinant of both equity and enterprise value. Section 3 examines the issues involved in selecting the earnings metric to forecast. Once an earnings metric has been chosen, the next question to ask is "How useful are historical accounting numbers for developing forecasts of that metric?" Sections 4 through 8 focus on this question. Section 4 discusses the general role of econometric modeling. Section 5 reviews time-series models. Section 6 examines the choices a researcher makes when using panel-data approaches and the author describes the advantages of these approaches. Section 7 reviews the role of accounting measurement in determining the usefulness of historical accounting numbers for developing forecasts of future earnings. Section 8 examines approaches for forecasting the higher moments of future earnings and section 9 provides a summary.
Evidence on the Tradeoff Between Real Manipulation and Accrual Manipulation: to 25; Pages:26 to 50; Pages:51 to 75; Pages:76 to 100; Pages:101 to 120
Author: Amy Yunzhi Zang
Publisher: ProQuest
ISBN: 9780549163251
Category :
Languages : en
Pages : 120
Book Description
Publisher: ProQuest
ISBN: 9780549163251
Category :
Languages : en
Pages : 120
Book Description
The C.F.A. Digest
Author: Institute of Chartered Financial Analysts
Publisher:
ISBN:
Category : Investments
Languages : en
Pages : 972
Book Description
Publisher:
ISBN:
Category : Investments
Languages : en
Pages : 972
Book Description
Handbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes)
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.
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.