Handbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes) PDF Download
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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: Cheng Few Lee
Publisher: World Scientific
ISBN: 9811202400
Category : Business & Economics
Languages : en
Pages : 5053
Get Book Here
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: Tanja Klettke
Publisher: Springer Science & Business
ISBN: 3658056347
Category : Business & Economics
Languages : en
Pages : 120
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Book Description
Financial analysts provide information in their research reports and thereby help forming expectations of a firm’s future business performance. Thus, it is essential to recognize analysts who provide the most precise forecasts and the accounting literature identifies characteristics that help finding the most accurate analysts. Tanja Klettke detects new relationships and identifies two new determinants of earnings forecast accuracy. These new determinants are an analyst’s “general forecast effort” and the “number of supplementary forecasts”. Within two comprehensive empirical investigations she proves these measures’ power to explain accuracy differences. Tanja Klettke’s research helps investors and researchers to identify more accurate earnings forecasts.
Author: United States. Advisory Committee on Corporate Disclosure
Publisher:
ISBN:
Category : Corporations
Languages : en
Pages : 894
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Book Description
Author: Joshua Ronen
Publisher: Springer Science & Business Media
ISBN: 0387257713
Category : Business & Economics
Languages : en
Pages : 587
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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?
Author: John B. Guerard, Jr.
Publisher: Springer Science & Business Media
ISBN: 1461452392
Category : Business & Economics
Languages : en
Pages : 245
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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.
Author: Francis A. Lees
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 56
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Book Description
Author: Amir Amel-Zadeh
Publisher: Routledge
ISBN: 1000066525
Category : Business & Economics
Languages : en
Pages : 331
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Book Description
Spending on M&A has, in aggregate, grown so fast that it has even overtaken capital expenditure on increasing and maintaining physical assets. Yet McKinsey, the leading management consultancy, reports that "Anyone who has researched merger success rates knows that roughly 70% fail". The idea that businesses might be using huge and increasing sums of shareholders’ money for an activity that more often than not leads to failure calls into question the information on which M&A decisions are based. This book presents statistical studies, case material, and standard-setters’ opinions on company accounting before, during, and after M&A. It documents the manipulation of annual accounts by acquirers ahead of share for share bids, biased forecasts of post-merger earnings by bidders, and devices to flatter earnings when recording the deal. It explores the challenges for standard-setters in regulating information flows during and after M&A, and for account-users wishing to learn from financial statements how a deal has affected performance. Drawing on a wide range of international examples, this readable book is targeted not just at accounting specialists but at anyone who is comfortable reading the serious financial press, is intrigued by what is going on in the massive M&A market, and is concerned with achieving better-informed M&A. As such it might be of particular interest to business executives, lawyers, bankers, and investors involved in M&A as well as graduate students interested in researching or learning about the role of accounting in M&A.
Author: Uptal Bhattacharya
Publisher:
ISBN: 9789616430258
Category :
Languages : en
Pages : 27
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Book Description
Author: Robert P. Gephart
Publisher: SAGE Publications, Incorporated
ISBN: 9780803930261
Category : Social Science
Languages : en
Pages : 72
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Book Description
This volume discusses ethnostatistics - the interpretative study of the construction and use of statistics in social research - and will be of equal interest to qualitative and quantitative researchers across the social sciences. On the understanding that the development of a statistic is inherently a qualitative act, the author shows how this act can be studied and analyzed. The interpretative factors in statistical work can be demonstrated at a variety of levels; Gephart shows how each can be usefully illuminated through the use of ethnostatistics to produce more effective, reflexive social research.
Author: Joshua Ronen
Publisher: Springer Science & Business Media
ISBN: 0387257691
Category : Business & Economics
Languages : en
Pages : 587
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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?
