Essentials of Excel VBA, Python, and R - Volume I: 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.

List of contents

Chapter 1. Introduction.- Chapter 2. Data Collection, Presentation, and Yahoo Finance.- Chapter 3. Histograms and the Rate of Returns of JPM and JNJ.- Chapter 4. Numerical Summary Measures on Stock Rates of Return and Market Rates of Return.- Chapter 5. Probability Concepts and their Analysis.- Chapter 6. Discrete Random Variables and Probability Distributions.- Chapter 7. The Normal and Lognormal Distributions.- Chapter 8. Sampling Distributions and Central Limit Theorem.- Chapter 9. Other Continuous Distributions.- Chapter 10. Estimation.- Chapter 11. Hypothesis Testing.- Chapter 12. Analysis of Variance and Chi-Square Tests.- Chapter 13. Simple Linear Regression and the Correlation Coefficient.- Chapter 14. Simple Linear Regression and Correlation: Analyses and Applications.- Chapter 15. Multiple Linear Regression.- Chapter 16. Residual and Regression Assumption Analysis.- Chapter 17. Nonparametric Statistics.- Chapter 18. Time Series: Analysis, Model, and Forecasting.- Chapter 19.Index Numbers and Stock Market Indexes.- Chapter 20. Sampling Surveys: Methods and Applications.- Chapter 21. Statistical Decision Theory.- Chapter 22. Sources of Risks and their Determination.- Chapter 23. Risk-Aversion, Capital Asset Allocation, and Markowitz Portfolio Selection Model.- Chapter 24. Capital Asset Pricing Model and Beta Forecasting.- Chapter 25. Single-Index Models for Portfolio Selection.- Chapter 26. Sharpe Performance Measure and Treynor Performance Measure Approach to Portfolio Analysis.

About the author

Cheng-Few Lee is a Distinguished Professor of Finance at Rutgers Business School, Rutgers University and was chairperson of the Department of Finance from 1988-1995. He has also served on the faculty of the University of Illinois (IBE Professor of Finance) and the University of Georgia. He has maintained academic and consulting ties in Taiwan, Hong Kong, China and the United States for the past three decades. He has been a consultant to many prominent groups including, the American Insurance Group, the World Bank, the United Nations, The Marmon Group Inc., Wintek Corporation, and Polaris Financial Group.

Professor Lee founded the Review of Quantitative Finance and Accounting (RQFA) in 1990 and the Review of Pacific Basin Financial Markets and Policies (RPBFMP) in 1998, and serves 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 Finance (1987-1989).

In thepast 42 years, Dr. Lee has written numerous textbooks ranging in subject matters from financial management to corporate finance, security analysis and portfolio management to financial analysis, planning and forecasting, and business statistics. In addition, he edited five popular books, Encyclopedia of Finance (with Alice C. Lee), Handbook of Quantitative Finance and Risk Management (with Alice C. Lee and John Lee), Handbook of Financial Econometrics and Statistics, Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning, and Handbook of Investment Analysis, Portfolio Management, and Financial Derivatives. Dr. Lee has also published more than 250 articles in more than 20 different journals in finance, accounting, economics, statistics, and management. Professor Lee was ranked the most published finance professor worldwide during the period 1953-2008.

Professor Lee was the intellectual force behind the creation of the new Masters of Quantitative Finance program at Rutgers University. This program began in 2001 and has been ranked as one of the top fifteen quantitative finance programs in the United States. Professor Lee started the Conference on Financial Economics and Accounting in 1989. This conference is a consortium of Rutgers University, New York University, Temple University, University of Maryland, Georgia State University, Tulane University, Indiana University, and University of Toronto. This conference is the most well-known conference in finance and accounting.

John C. Lee is Director of the Center for PBBEF Research. A Microsoft Certified Professional in Microsoft Visual Basic and Microsoft Excel VBA, Mr. 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 Presidentat Merrill Lynch, he is also the author of Business and Financial Statistics Using Minitab 12 and Microsoft Excel 97, as well as Financial Analysis, Planning and Forecasting with Cheng-Few Lee and Alice Lee.

Product details

• Authors: Cheng-Few Lee, John Lee
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 04.01.2024
• EAN: 9783031142383
• ISBN: 978-3-0-3114238-3
• No. of pages: 696
• Dimensions: 210 mm x 38 mm x 279 mm
• Illustrations: XVI, 696 p. 1113 illus., 1005 illus. in color.
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; Social sciences, law, business > Business > General, dictionaries