This eighth volume in the series covers a variety of topics in financial planning and forecasting, including: the change in earnings response coefficient around dividend omissions; estimating spin-off values; and, forbearance, deposit insurance, and the market value of savings and loan associations.

Advances in Financial Planning and Forecasting (Advances in Financial Planning and Forecasting, 8)

LEE, CHENG-FEW

Sutton, Steven G.

Cheng-Few Lee, Lee

Reference

Emerald Publishing Limited

"Advances in Quantitative Analysis of Finance and Accounting" is an annual publication designed to disseminate developments in the quantitative analysis of finance and accounting. The publication 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 and applied research in the financial community and the accounting profession. The papers in this volume cover a wide range of topics including default risk premiums, multi-period contracts, stock market, impact of earnings change on stock price, bank regulation, dividend effect of closed-end mutual funds, income smoothing, and inflation accounting.

Advances in Quantitative Analysis of Finance and Accounting (Advances in Quantitative Analysis of Finance and Accounting, 9)

Business & Money

Economics

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.

Statistics for Business and Financial Economics

Lee, John C.

LEE, ALICE C

Springer

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 Statisticsintroduces 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.

Financial Econometrics, Mathematics and Statistics: Theory, Method and Application

Lee, John

Chen, Hong-Yi

Essentials of Excel VBA, Python, and R: Volume I: Financial Statistics and Portfolio Analysis

Education & Reference

Essentials of Excel VBA, Python, and R: Volume II: Financial Derivatives, Risk Management and Machine Learning

Chang, Jow-Ran

Kao, Lie Jane

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.

Essentials of Excel, Excel VBA, SAS and Minitab for Statistical and Financial Analyses

Tai, Tzu

News Professor 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.

STATISTICS FOR BUSINESS AND FINANCIAL ECONOMICS (SECOND EDITION)

World Scientific Publishing Company

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