From the reviews:
As can be seen from the chapters’ contents, the breadth of topics covered of this book is impressive. Overall, this is a very nice book for introducing students to a variety of models for analyzing financial data." Journal of Statistical Software, June 2004
"The author, a fellow of the Institute of Mathematical Statistics, presents a solid dose of theory and methodology." Technometrics, May 2005
"This book is a text for an undergraduate course in data analysis focused on financial applications. It is not an S-Plus book but rather covers the main problems arising in data analysis techniques in financial engineering..As the book is based on lectures for a course on statsitical analysis of financial data, a trade off between the depth at which the toics are presented and the computational implementations are kept in balance. This textbook will be very helpful for a general course in financial engineering." The American Statistician, November 2005
"This textbook appears to be primarily intended as an introduction to statistical analysis of financial data … . the book provides the reader with a practical computational approach to financial analytical techniques. It should appeal to instructors who prefer an applied-based text to a theoretical one. I enjoyed the use of simulation based illustrations and will be using some of the ideas in the future. The book could be used for teaching a third-year undergraduate or post-graduate (honours level), course in a statistics department or in a program designed for finance." (Gary D Sharp, SASA News, March, 2006)
"S-plus, a popular software for statisticians, has many books devoted to teach it. … the book would be very good choice as a lab manual providing many useful rules of thumb. … the book doubtlessly provides a pleasant introduction to statistics using S-plus. The friendly tone throughout certainly adds to the charm. Simple yet detailed exercises at the end of each chapter offer a gentle massage for the brain." (Arnab Chakraborty, Sankhya, Vol. 66 (3), 2004)
"This is an excellent text, written by a well known expert in the field, dealing with statistical analysis of financial data. … As remarked by the author, the emphasis of the book is on graphical and computational methods for the analysis of financial data. … The book is clearly written and remarkably free of typos. I believe it will be a very useful addition to the existing books and I highly recommend it." (Pedro A. Morettin, Zentralblatt MATH, Vol. 1055, 2005)
"This is a timely book on modern data analysis with a difference: the examples and applications are predominantly taken from Finance Engineering. … This book will help fill a statistical gap in the otherwise heavily theoretical literature in mathematical finance." (D. L. McLeish, Short Book Reviews, Vol. 24 (2), 2004)
"The seven chapters are an excellent resource to anyone wishing to learn more about the application of statistics to financial data. … A comprehensive reference section is given and the book has the S-PLUS codes that are needed to perform the statistical modelling. … The reference section is extremely useful and comprehensive. Libraries should be encouraged to purchase copies of this text for undergraduate and post-graduate students in finance and statistics." (Isaac Dialsingh, Significance, Vol. 3 (3), 2006)
Although there are many books on mathematical finance, few deal with the statistical aspects of modern data analysis as applied to financial problems. This book fills this gap by addressing some of the most challenging issues facing any financial engineer. It shows how sophisticated mathematics and modern statistical techniques can be used in concrete financial problems.
Concerns of risk management are addressed by the control of extreme values, the fitting of distributions with heavy tails, the computation of values at risk (VaR), and other measures of risk. Data description techniques such as principal component analysis (PCA), smoothing, and regression are applied to the construction of yield and forward curve. Nonparametric estimation and nonlinear filtering are used for option pricing and earnings prediction.
The book is intended for undergraduate students majoring in financial engineering, or graduate students in a Master in finance or MBA program. Because it was designed as a teaching vehicle, it is sprinkled with practical examples using market data, and each chapter ends with exercises. Practical examples are solved in the computing environment of S-PLUS. They illustrate problems occurring in the commodity and energy markets, the fixed income markets as well as the equity markets, and even some new emerging markets like the weather markets.
The book can help quantitative analysts by guiding them through the details of statistical model estimation and implementation. It will also be of interest to researchers wishing to manipulate financial data, implement abstract concepts, and test mathematical theories, especially by addressing practical issues that are often neglected in the presentation of the theory.
Rene Carmona is the Paul M. Wythes '55 Professor of Engineering and Finance at Princeton University in the department of Operations Research and Financial Engineering and Director of Graduate Studies of the Bendheim Center for Finance. His publications include over seventy articles and six books in probability and statistics. He was elected Fellow of the Institute of Mathematical Statistics in 1984, and he is on the editorial board of several peer-reviewed journals and book series. Professor Carmona has developed computer programs for teaching of statistics, for research in signal analysis, and more recently, he contributed the library EVANESCE for the analysis of heavy tail distributions and copulas. The latter was included in the latest version of S-Plus. He has worked for many years on energy and weather derivatives, and he is recognized as a leading researcher and consultant in this area.
The book was completely brand new. The shipping decent, so overall a pretty great purchase.Published on October 6, 2007 by E
After spending big money for this book, I was shocked I had to shell out even more money to get the data and S-plus scripts. Her book is like an old style teaser. Read morePublished on April 18, 2004