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Financial Econometrics, Mathematics and Statistics

Theory, Method and Application

  • Textbook
  • © 2019


  • Organizes a dynamic presentation of concepts from C.F. Lee's earlier successful handbook ideal for any advanced applied econometrics and statistics course
  • Covers topics such as heteroskedasticity, regression, simultaneous equation models, panel data analysis, time series analysis, and generalized method of moments.
  • Contains in-depth examples and problem sets modeled after "real world" financial analysis

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About this book

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.  ​

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Table of contents (24 chapters)

  1. Regression and Financial Econometrics

  2. Time-Series Analysis and Its Applications

  3. Statistical Distributions, Option Pricing Model and Risk Management


“The main readers of the book are seen as upper-undergraduate and graduate students in finance, economics, and statistics. But practitioners in financial analysis will find much use in this. The book contains many examples of statistical analysis of data, both hypothetical and real; computational implementation codes for various algorithms … . All these features and themes, as well as a rigorous explanation make this book an exclusive item in the sector of education and professional literature.” (Vladimir Gorbunov, zbMATH 1460.62001, 2021)

Authors and Affiliations

  • Department of Finance and Economics Rutgers Business School, Rutgers University, Piscataway, USA

    Cheng-Few Lee

  • Department of Finance, National Chengchi University, Taipei, Taiwan

    Hong-Yi Chen

  • Center for PBBEF Research, Morris Plains, USA

    John Lee

About the authors

Cheng-Few Lee is a Distinguished Professor of Finance at Rutgers Business School, where he once served as  chairperson of the Department. He has maintained academic and consulting ties in Taiwan, Hong Kong, China and the United States for the past three decades and  has been a consultant to many prominent groups including the American Insurance Group, the World Bank, and the United Nations.  Lee founded the Review of Quantitative Finance and Accounting in 1990 and the Review of Pacific Basin Financial Markets and Policies in 1998, and continues to serve as managing editor for both journals. He was also a co-editor of the Financial Review (1985–1991) and the Quarterly Review of Economics and Business (1987–1989).  Having published more than 200 articles in more than twenty different journals in finance, accounting, economics, statistics, and management,  Lee has been ranked the most published finance professor worldwide during 1953–2008. 


Hong-Yi Chen is Assistant Professor at the NCCU College of Commerce. His research expertise is in investments, asset pricing, and corporate finance. He has co-authored several papers in journals such as  Springer's Review of Quantitative Finance and Accounting, as well as Elsevier's Journal of Corporate Finance.

John C. Lee is Director of the Center for PBBEF Research. A Microsoft Certified Professional in Microsoft Visual Basic and Microsoft Excel VBA, he has a Bachelors and Masters degree in accounting from the University of Illinois at Urbana-Champaign. Lee  has worked over 20 years in both the business and technical fields as an accountant, auditor, systems analyst, as well as a business software developer. Formerly, the Senior Technology Officer at the Chase Manhattan Bank and Assistant Vice President at Merrill Lynch, he is also the author of the book on how to use MINITAB and Microsoft Excel to do statistical analysis. In addition, he also published Financial Analysis, Planning and Forecasting with Cheng-Few Lee and Alice Lee. 

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