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by Cheng-Few Lee (Author), Hong-Yi Chen (Author), John Lee (Author)
About the Author
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.
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.
Brief contents
1 Introduction to Financial Econometrics, Mathematics, and Statistics 1
Part I Regression and Financial Econometrics
2 Multiple Linear Regression. 19
3 Other Topics in Applied Regression Analysis 55
4 Simultaneous Equation Models. 115
5 Econometric Approach to Financial Analysis, Planning, and Forecasting 125
6 Fixed Effects Versus Random Effects in Finance Research 159
7 Alternative Methods to Deal with Measurement Error. 181
8 Three Alternative Methods in Testing Capital Asset Pricing Model 211
9 Spurious Regression and Data Mining in Conditional Asset Pricing Models 243
Part II Time-Series Analysis and Its Applications
10 Time Series: Analysis, Model, and Forecasting 279
11 Hedge Ratio and Time-Series Analysis 317
Part III Statistical Distributions, Option Pricing Model and Risk Management
12 The Binomial, Multinomial Distributions, and Option Pricing Model 357
13 Two Alternative Binomial Option Pricing Model Approaches to Derive Black–Scholes Option Pricing Model 379
14 Normal, Lognormal Distribution, and Option Pricing Model 393
15 Copula, Correlated Defaults, and Credit VaR. 419
16 Multivariate Analysis: Discriminant Analysis and Factor Analysis 439
Part IV Statistics, Itô’s Calculus and Option Pricing Model
17 Stochastic Volatility Option Pricing Models 461
18 Alternative Methods to Estimate Implied Variance: Review and Comparison 473
19 Numerical Valuation of Asian Options with Higher Moments in the Underlying Distribution 491
20 Itô’s Calculus: Derivation of the Black–Scholes Option Pricing Model 517
21 Alternative Methods to Derive Option Pricing Models 541
22 Constant Elasticity of Variance Option Pricing Model: Integration and Detailed Derivation. 571
23 Option Pricing and Hedging Performance Under Stochastic Volatility and Stochastic Interest Rates 583
24 Nonparametric Method for European Option Bounds 623
Author Index 643
Subject Index. 653
Pages: 655 pages
Publisher: Springer; 1st ed. 2019 edition (July 10, 2019)
Language: English
ISBN-10: 1493994271
ISBN-13: 978-1493994274
Springer__Financial Econometrics, Mathematics and Statistics.pdf
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