Financial Statement Analysis and the Prediction of Financial Distress PDF Download

Author: William H. Beaver
Publisher: Now Publishers Inc
ISBN: 1601984243
Category : Business & Economics
Languages : en
Pages : 89

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Book Description
Financial Statement Analysis and the Prediction of Financial Distress discusses the evolution of three main streams within the financial distress prediction literature: the set of dependent and explanatory variables used, the statistical methods of estimation, and the modeling of financial distress. Section 1 discusses concepts of financial distress. Section 2 discusses theories regarding the use of financial ratios as predictors of financial distress. Section 3 contains a brief review of the literature. Section 4 discusses the use of market price-based models of financial distress. Section 5 develops the statistical methods for empirical estimation of the probability of financial distress. Section 6 discusses the major empirical findings with respect to prediction of financial distress. Section 7 briefly summarizes some of the more relevant literature with respect to bond ratings. Section 8 presents some suggestions for future research and Section 9 presents concluding remarks.

Author: Michael Samonas
Publisher: John Wiley & Sons
ISBN: 1118921097
Category : Business & Economics
Languages : en
Pages : 242

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Book Description
Risk analysis has become critical to modern financial planning Financial Forecasting, Analysis and Modelling provides a complete framework of long-term financial forecasts in a practical and accessible way, helping finance professionals include uncertainty in their planning and budgeting process. With thorough coverage of financial statement simulation models and clear, concise implementation instruction, this book guides readers step-by-step through the entire projection plan development process. Readers learn the tools, techniques, and special considerations that increase accuracy and smooth the workflow, and develop a more robust analysis process that improves financial strategy. The companion website provides a complete operational model that can be customised to develop financial projections or a range of other key financial measures, giving readers an immediately-applicable tool to facilitate effective decision-making. In the aftermath of the recent financial crisis, the need for experienced financial modelling professionals has steadily increased as organisations rush to adjust to economic volatility and uncertainty. This book provides the deeper level of understanding needed to develop stronger financial planning, with techniques tailored to real-life situations. Develop long-term projection plans using Excel Use appropriate models to develop a more proactive strategy Apply risk and uncertainty projections more accurately Master the Excel Scenario Manager, Sensitivity Analysis, Monte Carlo Simulation, and more Risk plays a larger role in financial planning than ever before, and possible outcomes must be measured before decisions are made. Uncertainty has become a critical component in financial planning, and accuracy demands it be used appropriately. With special focus on uncertainty in modelling and planning, Financial Forecasting, Analysis and Modelling is a comprehensive guide to the mechanics of modern finance.

Author: Steven J. Monahan
Publisher: Foundations and Trends (R) in Accounting
ISBN: 9781680834505
Category :
Languages : en
Pages : 124

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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.

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: IEEE Staff
Publisher:
ISBN: 9781728143965
Category :
Languages : en
Pages :

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Book Description
INDIN focuses on recent developments, deployments, technology trends, and research results in Industrial Informatics related fields from both industry and academia

Author: Wayne Ferson
Publisher: MIT Press
ISBN: 0262039370
Category : Business & Economics
Languages : en
Pages : 497

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Book Description
An introduction to the theory and methods of empirical asset pricing, integrating classical foundations with recent developments. This book offers a comprehensive advanced introduction to asset pricing, the study of models for the prices and returns of various securities. The focus is empirical, emphasizing how the models relate to the data. The book offers a uniquely integrated treatment, combining classical foundations with more recent developments in the literature and relating some of the material to applications in investment management. It covers the theory of empirical asset pricing, the main empirical methods, and a range of applied topics. The book introduces the theory of empirical asset pricing through three main paradigms: mean variance analysis, stochastic discount factors, and beta pricing models. It describes empirical methods, beginning with the generalized method of moments (GMM) and viewing other methods as special cases of GMM; offers a comprehensive review of fund performance evaluation; and presents selected applied topics, including a substantial chapter on predictability in asset markets that covers predicting the level of returns, volatility and higher moments, and predicting cross-sectional differences in returns. Other chapters cover production-based asset pricing, long-run risk models, the Campbell-Shiller approximation, the debate on covariance versus characteristics, and the relation of volatility to the cross-section of stock returns. An extensive reference section captures the current state of the field. The book is intended for use by graduate students in finance and economics; it can also serve as a reference for professionals.

Author: Papadakis, Stylianos
Publisher: IGI Global
ISBN: 179984806X
Category : Business & Economics
Languages : en
Pages : 270

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Book Description
The prediction of the valuation of the “quality” of firm accounting disclosure is an emerging economic problem that has not been adequately analyzed in the relevant economic literature. While there are a plethora of machine learning methods and algorithms that have been implemented in recent years in the field of economics that aim at creating predictive models for detecting business failure, only a small amount of literature is provided towards the prediction of the “actual” financial performance of the business activity. Machine Learning Applications for Accounting Disclosure and Fraud Detection is a crucial reference work that uses machine learning techniques in accounting disclosure and identifies methodological aspects revealing the deployment of fraudulent behavior and fraud detection in the corporate environment. The book applies machine learning models to identify “quality” characteristics in corporate accounting disclosure, proposing specific tools for detecting core business fraud characteristics. Covering topics that include data mining; fraud governance, detection, and prevention; and internal auditing, this book is essential for accountants, auditors, managers, fraud detection experts, forensic accountants, financial accountants, IT specialists, corporate finance experts, business analysts, academicians, researchers, and students.

Author: Stephen H. Penman
Publisher:
ISBN: 9780071267809
Category : Financial statements
Languages : en
Pages : 754

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Book Description
Valuation is at the heart of investing. A considerable part of the information for valuation is in the financial statements.Financial Statement Analysis and Security Valuation, 5 e by Stephen Penman shows students how to extract information from financial statements and use that data to value firms. The 5th edition shows how to handle the accounting in financial statements and use the financial statements as a lens to view a business and assess the value it generates.

Author: Max Kuhn
Publisher: Springer Science & Business Media
ISBN: 1461468493
Category : Medical
Languages : en
Pages : 595

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Book Description
Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.

Author: Philip M J Reckers
Publisher: Elsevier
ISBN: 0080471889
Category : Business & Economics
Languages : en
Pages : 308

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Book Description
Now in its 20th edition, "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. This volume of "Advances in Accounting" includes articles reflective of recent economic distress: articles on the effects of post bankruptcy financial reporting, measurement of decline in earnings persistence, re-estimations of bankruptcy prediction models, and an understanding of new assurance needs. It also looks at trends of significance to academics (trends in research and dissertations focus) and practitioners (trends in IS audits). With this 20th volume, "Advances in Accounting" makes a new commitment to the global arena by introduction of an International Section and a new international associate editor. As never before, the accounting profession is seeking ways to reinvent itself and recapture relevance and credibility. AIA likewise continues to champion change through this revised global editorial commitment.