Cheng Few Lee

Statistics for Business and Financial Economics, 3rd edition is the definitive Business Statistics book to use Finance, Economics, and Accounting data throughout the entire book. Therefore, this book gives students an understanding of how to apply the methodology of statistics to real world situations. In particular, this book shows how descriptive statistics, probability, statistical distributions, statistical inference, regression methods, and statistical decision theory can be used to analyze individual stock price, stock index, stock rate of return, market rate of return, and decision making. In addition, this book also shows how time-series analysis and the statistical decision theory method can be used to analyze accounting and financial data. In this fully-revised edition, the real world examples have been reconfigured and sections have been edited for better understanding of the topics. On the Springer page for the book, the solution manual, test bank and powerpoints are available for download.

Security Analysis, Portfolio Management, and Financial Derivatives integrates the many topics of modern investment analysis. It provides a balanced presentation of theories, institutions, markets, academic research, and practical applications, and presents both basic concepts and advanced principles. Topic coverage is especially broad: in analyzing securities, the authors look at stocks and bonds, options, futures, foreign exchange, and international securities. The discussion of financial derivatives includes detailed analyses of options, futures, option pricing models, and hedging strategies. A unique chapter on market indices teaches students the basics of index information, calculation, and usage and illustrates the important roles that these indices play in model formation, performance evaluation, investment strategy, and hedging techniques. Complete sections on program trading, portfolio insurance, duration and bond immunization, performance measurements, and the timing of stock selection provide real-world applications of investment theory. In addition, special topics, including equity risk premia, simultaneous-equation approach for security valuation, and Itô's calculus, are also included for advanced students and researchers.

NewsProfessor Cheng-Few Lee ranks #1 based on his publications in the 26 core finance journals, and #163 based on publications in the 7 leading finance journals (Source: Most Prolific Authors in the Finance Literature: 1959-2008 by Jean L Heck and Philip L Cooley (Saint Joseph's University and Trinity University).Based on the authors' extensive teaching, research and business experiences, this book reviews, discusses and integrates both theoretical and practical aspects of financial planning and forecasting. The book is divided into six parts: Information and Methodology for Financial Analysis, Alternative Finance Theories and Their Application, Capital Budgeting and Leasing Decisions, Corporate Policies and Their Interrelationships, Short-term Financial Decisions, Financial Planning and Forecasting, and Overview.The theories used in this book are pre-Modigliani-Miller Theorem, Modigliani-Miller Theorem, Capital Asset Pricing Model and Arbitrage Pricing Theory, and Option Pricing Theory. The interrelationships among these theories are carefully analyzed. Meaningful real-world examples of using these theories are discussed step-by-step, with relevant data and methodology. Alternative planning and forecasting models are also used to show how the interdisciplinary approach is helpful in making meaningful financial management decisions.

NewsProfessor Cheng-Few Lee ranks #1 based on his publications in the 26 core finance journals, and #163 based on publications in the 7 leading finance journals (Source: Most Prolific Authors in the Finance Literature: 1959-2008 by Jean L Heck and Philip L Cooley (Saint Joseph's University and Trinity University).This is an extensively revised edition of a popular statistics textbook for business and economics students. The first edition has been adopted by universities and colleges worldwide, including New York University, Carnegie Mellon University and UCLA.Designed for upper-level undergraduates, MBA and other graduate students, this book closely integrates various statistical techniques with concepts from business, economics and finance and clearly demonstrates the power of statistical methods in the real world of business. While maintaining the essence of the first edition, the new edition places more emphasis on finance, economics and accounting concepts with updated sample data. Students will find this book very accessible with its straightforward language, ample cases, examples, illustrations and real-life applications. The book is also useful for financial analysts and portfolio managers.

This advanced textbook for business statistics teaches, statistical analyses and research methods utilizing business case studies and financial data with the applications of Excel VBA, Python and R. Each chapter engages the reader with sample data drawn from individual stocks, stock indices, options, and futures. Now in its second edition, it has been expanded into two volumes, each of which is devoted to specific parts of the business analytics curriculum. To reflect the current age of data science and machine learning, the used applications have been updated from Minitab and SAS to Python and R, so that readers will be better prepared for the current industry.This second volume is designed for advanced courses in financial derivatives, risk management, and machine learning and financial management. In this volume we extensively use Excel, Python, and R to analyze the above-mentioned topics. It is also a comprehensive reference for active statistical finance scholars and business analysts who are looking to upgrade their toolkits. Readers can look to the first volume for dedicated content on financial statistics, and portfolio analysis.

This advanced textbook for business statistics teaches, statistical analyses and research methods utilizing business case studies and financial data, with the applications of Excel VBA, Python and R. Each chapter engages the reader with sample data drawn from individual stocks, stock indices, options, and futures. Now in its second edition, it has been expanded into two volumes, each of which is devoted to specific parts of the business analytics curriculum. To reflect the current age of data science and machine learning, the used applications have been updated from Minitab and SAS to Python and R, so that readers will be better prepared for the current industry.This first volume is designed for advanced courses in financial statistics, investment analysis and portfolio management. It is also a comprehensive reference for active statistical finance scholars and business analysts who are looking to upgrade their toolkits. Readers can look to the second volume for dedicated content on financial derivatives, risk management, and machine learning.

Futures and Options are concerned with the valuation of derivatives and their application to hedging and speculating investments. This book contains 22 chapters and is divided into five parts. Part I contains an overview including a general introduction as well as an introduction to futures, options, swaps, and valuation theories. Part II: Forwards and Futures discusses futures valuation, the futures market, hedging strategies, and various types of futures. Part III: Option Theories and Applications includes both the basic and advanced valuation of options and option strategies in addition to index and currency options. Part IV: Advanced Analyses of Options takes a look at higher level strategies used to quantitatively approach the analysis of options. Part V: Special Topics of Options and Futures covers the applications of more obscure and alternative methods in derivatives as well as the derivation of the Black-Scholes Option Pricing Model.This book applies an active interdisciplinary approach to presenting the material; in other words, three projects involving the use of real-world financial data on derivative, in addition to homework assignments, are made available for students in this book.

Futures and Options are concerned with the valuation of derivatives and their application to hedging and speculating investments. This book contains 22 chapters and is divided into five parts. Part I contains an overview including a general introduction as well as an introduction to futures, options, swaps, and valuation theories. Part II: Forwards and Futures discusses futures valuation, the futures market, hedging strategies, and various types of futures. Part III: Option Theories and Applications includes both the basic and advanced valuation of options and option strategies in addition to index and currency options. Part IV: Advanced Analyses of Options takes a look at higher level strategies used to quantitatively approach the analysis of options. Part V: Special Topics of Options and Futures covers the applications of more obscure and alternative methods in derivatives as well as the derivation of the Black-Scholes Option Pricing Model.This book applies an active interdisciplinary approach to presenting the material; in other words, three projects involving the use of real-world financial data on derivative, in addition to homework assignments, are made available for students in this book.

This advanced textbook for business statistics teaches, statistical analyses and research methods utilizing business case studies and financial data with the applications of Excel VBA, Python and R. Each chapter engages the reader with sample data drawn from individual stocks, stock indices, options, and futures. Now in its second edition, it has been expanded into two volumes, each of which is devoted to specific parts of the business analytics curriculum. To reflect the current age of data science and machine learning, the used applications have been updated from Minitab and SAS to Python and R, so that readers will be better prepared for the current industry.This second volume is designed for advanced courses in financial derivatives, risk management, and machine learning and financial management. In this volume we extensively use Excel, Python, and R to analyze the above-mentioned topics. It is also a comprehensive reference for active statistical finance scholars and business analysts who are looking to upgrade their toolkits. Readers can look to the first volume for dedicated content on financial statistics, and portfolio analysis.

This advanced textbook for business statistics teaches, statistical analyses and research methods utilizing business case studies and financial data, with the applications of Excel VBA, Python and R. Each chapter engages the reader with sample data drawn from individual stocks, stock indices, options, and futures. Now in its second edition, it has been expanded into two volumes, each of which is devoted to specific parts of the business analytics curriculum. To reflect the current age of data science and machine learning, the used applications have been updated from Minitab and SAS to Python and R, so that readers will be better prepared for the current industry.This first volume is designed for advanced courses in financial statistics, investment analysis and portfolio management. It is also a comprehensive reference for active statistical finance scholars and business analysts who are looking to upgrade their toolkits. Readers can look to the second volume for dedicated content on financial derivatives, risk management, and machine learning.

Corporate finance is concerned with how to make capital investment decisions (capital budgeting); how to finance company activities, including new investments; and how to make dividend payment decisions. This book will lecture on important topics for corporate finance, which will cover methods, theory, and policy decisions. The topics which will be addressed in this book include how streams of cash flows are valued, how financial managers evaluate investment opportunities, how financial statements are used to evaluate a company's financial condition and its market value, how a manager chooses between mutually exclusive opportunities, and how they evaluate different types of investment. This book will also discuss the treatment of risk when evaluating a project and the required returns on a project. Alternative sources of funds used to finance new projects, which include internal and external sources of funds, will be theoretically and empirically demonstrated. Lastly, long-term financial planning will be discussed.

This rigorous textbook introduces graduate students to the principles of econometrics and statistics with a focus on methods and applications in financial research. Financial Econometrics, Mathematics, and Statistics introduces tools and methods important for both finance and accounting that assist with asset pricing, corporate finance, options and futures, and conducting financial accounting research. Divided into four parts, the text begins with topics related to regression and financial econometrics. Subsequent sections describe time-series analyses; the role of binomial, multi-nomial, and log normal distributions in option pricing models; and the application of statistics analyses to risk management. The real-world applications and problems offer students a unique insight into such topics as heteroskedasticity, regression, simultaneous equation models, panel data analysis, time series analysis, and generalized method of moments. Written by leading academics in the quantitative finance field, allows readers to implement the principles behind financial econometrics and statistics through real-world applications and problem sets. This textbook will appeal to a less-served market of upper-undergraduate and graduate students in finance, economics, and statistics. ?

This memoir presents a special look into Professor Cheng-Few Lee's formative childhood years, his distinguished career as a respected scholar and conference organizer, and his substantial experience in the fields of education and policy-making. It shares the innovative methods and forward-looking educational philosophy that underpin the rigorous training of his students in finance and accounting. This memoir also reflects upon Professor Lee's life experiences, and his involvement in business consulting and government policy-making. Readers will enjoy this private retrospection into the memories, experiences, and philosophy of this humble man, who is counted among the most published finance professors and experienced journal editors in the world.

This memoir presents a special look into Professor Cheng-Few Lee's formative childhood years, his distinguished career as a respected scholar and conference organizer, and his substantial experience in the fields of education and policy-making. It shares the innovative methods and forward-looking educational philosophy that underpin the rigorous training of his students in finance and accounting. This memoir also reflects upon Professor Lee's life experiences, and his involvement in business consulting and government policy-making. Readers will enjoy this private retrospection into the memories, experiences, and philosophy of this humble man, who is counted among the most published finance professors and experienced journal editors in the world.

This introductory textbook for business statistics teaches statistical analysis and research methods via business case studies and financial data using Excel, Minitab, and SAS. Every chapter in this textbook engages the reader with data of individual stock, stock indices, options, and futures. One studies and uses statistics to learn how to study, analyze, and understand a data set of particular interest. Some of the more popular statistical programs that have been developed to use statistical and computational methods to analyze data sets are SAS, SPSS, and Minitab. Of those, we look at Minitab and SAS in this textbook. One of the main reasons to use Minitab is that it is the easiest to use among the popular statistical programs. We look at SAS because it is the leading statistical package used in industry. We also utilize the much less costly and ubiquitous Microsoft Excel to do statistical analysis, as the benefits of Excel have become widely recognized in the academic world and its analytical capabilities extend to about 90 percent of statistical analysis done in the business world. We demonstrate much of our statistical analysis using Excel and double check the analysis and outcomes using Minitab and SAS—also helpful in some analytical methods not possible or practical to do in Excel.

This book is an introduction-level text that reviews, discusses, and integrates both theoretical and practical corporate analysis and planning. The field can be divided into five parts: (1) Information and Methodology for Financial Analysis; (2) Alternative Finance Theories and Cost of Capital; (3) Capital Budgeting and Leasing Decisions; (4) Corporate Policies and their Interrelationships; (5) Financial Planning and Forecasting.The theories used and discussed in this book can be grouped into the following classical theoretical areas of corporate finance: (1) Pre-M&M Theory, (2) M&M Theory, (3) CAPM, and (4) Option Pricing Theory (OPT). The interrelationships among these theories are carefully analyzed. Real world examples are used to enrich the learning experience; and alternative planning and forecasting models are used to show how the interdisciplinary approach can be used to make meaningful financial-management decisions.In this third edition, we have extensively updated and expanded the topics of financial analysis, planning and forecasting. New chapters were added, and some chapters combined to present a holistic view of the subject and much of the data revised and updated.

NewsProfessor Cheng-Few Lee ranks #1 based on his publications in the 26 core finance journals, and #163 based on publications in the 7 leading finance journals (Source: Most Prolific Authors in the Finance Literature: 1959-2008 by Jean L Heck and Philip L Cooley (Saint Joseph's University and Trinity University).Advances in Quantitative Analysis of Finance and Accounting, New Series (AQAFANS) is a continuation (with new features) of the similarly titled book series that was previously published by JAI Press from 1991. AQAFANS is an annual publication designed to disseminate developments in the quantitative analysis of finance and accounting. It 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, applied research in the financial community, and the accounting profession.