Modeling Financial Time Series with S-PLUS® [Paperback]

Eric Zivot (Author), Jiahui Wang (Author)

Book Description

Publication Date: December 8, 2005

This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics. It is the first book to show the power of S-PLUS for the analysis of time series data. It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts. This edition covers S+FinMetrics 2.0 and includes new chapters.

Editorial Reviews

Review

From the reviews of the second edition: "It provides theoretical and empirical discussions on exhaustive topics in modern financial econometrics, statistics and time series. … it is definitely a good reference book for use in studying and/or researching in modern empirical finance … ." (T. S. Wirjanto, Short Book Reviews, Vol. 26 (1), 2006) "...It is a pleasure to strongly recommend this text, and to include statisticians such as myself among the pleased audience." (Thomas L. Burr for Techommetrics, Vol. 49, No. 1, February 2007) "This book has a double function. First, it serves as a guide to models and estimation methods for extracting information from financial time series, and second, as a user's guide for Insightful's S+FinMetrics package. That makes it interesting for mainly two communities of readers: the academic community in econometrics, statistics and finance, and the pracitioners in the finance industry. ...In summary this book is excellent to learn key methods and corresponding S+FinMetrics functions to analyze financial time series." (Valerie Chavez-Dumoulin for Journal of Statistical Software, Vol. 17, February 2007) "This is the second edition of the book devoted to a new 2.0 version of S+FinMetrix module of statistical functions for financial time series analysis and financial econometrics. It can be used as the users guide for S+FinMetrix and as a general reference for financial statistics on S-Plus. The book covers a variety of topics in statistical analysis and visualization of time series … ." (R. E. Maiboroda, Zentralblatt MATH, Vol. 1092 (18), 2006) "Analyzing financial time series has been enjoying increasing popularity over the last decade. … The book under review covers many of these different theories and methods. … The intended audience comprises both researchers and practitioners in the finance industry, academic researchers in financial econometrics, but also advanced and graduate students. … As almost every relevant topic from financial econometrics is under consideration, this book is a must for every person with empirical interest who has decided to use S, S-PLUS and S+FinMetrics as underlying platform." (Matthias Fischer, Allgemeines Statistisches Archiv, Vol. 90, 2006) "This book is a guide on how to analyze and model financial time series data using S-PLUS and S-FinMetrics. … The book is aimed for a wide audience of workers in the areas of empirical finance … and many researchers in economics and finance, marketing, and even management. This publication can also be an important tool for graduate students in the areas of statistics, economics, finance, and operations research. … In conclusion … a much needed book on financial time series … ." (Stergios B. Fotopoulos, Technometrics, Vol. 49 (3), August, 2007) "This second edition is a compilation of methods for analyzing financial time series using S-PLUS and the S-PLUS module S+FinMetrics. … The sheer number of time series topics covered by the book is impressive … . if you are a knowledgeable reader looking for a brief exposition of many common and current results, along with illuminating applications and illustrations with S-PLUS and S+FinMetrics, you will be pleased." (Jane L. Harvill, Sky & Telescope, November, 2007)

From the Back Cover

The field of financial econometrics has exploded over the last decade. This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics. This is the first book to show the power of S-PLUS for the analysis of time series data. It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts. This second edition is updated to cover S+FinMetrics 2.0 and includes new chapters on copulas, nonlinear regime switching models, continuous-time financial models, generalized method of moments, semi-nonparametric conditional density models, and the efficient method of moments. Eric Zivot is an associate professor and Gary Waterman Distinguished Scholar in the Economics Department, and adjunct associate professor of finance in the Business School at the University of Washington. He regularly teaches courses on econometric theory, financial econometrics and time series econometrics, and is the recipient of the Henry T. Buechel Award for Outstanding Teaching. He is an associate editor of Studies in Nonlinear Dynamics and Econometrics. He has published papers in the leading econometrics journals, including Econometrica, Econometric Theory, the Journal of Business and Economic Statistics, Journal of Econometrics, and the Review of Economics and Statistics. Jiahui Wang is a Principal and Trading Research Officer at Barclays Global Investors. He received a Ph.D. in Economics from the University of Washington in 1997. He has published in leading econometrics journals such as Econometrica and Journal of Business and Economic Statistics, and is the Principal Investigator of National Science Foundation SBIR grants. In 2002 Dr. Wang was selected as one of the "2000 Outstanding Scholars of the 21st Century" by International Biographical Centre.

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Product Details

• Paperback: 1024 pages
• Publisher: Springer; 2nd edition (December 8, 2005)
• Language: English
• ISBN-10: 0387279652
• ISBN-13: 978-0387279657
• Product Dimensions: 9.2 x 6.1 x 2 inches
• Shipping Weight: 3.1 pounds (View shipping rates and policies)
• Average Customer Review: 4.0 out of 5 stars  See all reviews (8 customer reviews)
• Amazon Best Sellers Rank: #673,179 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

16 of 21 people found the following review helpful:

5.0 out of 5 stars This is the best applied financial econometrics book., October 28, 2002

By 

"yin_luo" (Toronto, ON CANADA) - See all my reviews

This review is from: Modeling Financial Time Series with S-PLUS (Paperback)

This is an excellent book on financial econometrics, very practical yet rigorous. I wish all econometrics/statistics textbook could like this. Basic theory followed by practical examples - real life examples, not simplified ones like in other books. The authors gave detailed instructions on how to implement various econometric models, i.e. multi-factor models, GARCH, MGARCH, long memory models, state-space, etc. Most econometrics textbooks are at two extremes, they are either too theoretical (you still don't know how to put those models in real life), or too simple (lack of mathematical rigor and without advanced applications). This book is a combination of both worlds, computer codes/math models, and real life examples (some really good ones). A lot of cutting-edge techniques and advanced topics are also covered.

6 of 7 people found the following review helpful:

5.0 out of 5 stars Great applied econometrics book, even without FinMetrics!, October 8, 2006

By 

B. Peterson (Chicago, IL USA) - See all my reviews
(REAL NAME)   

This review is from: Modeling Financial Time Series with S-PLUS® (Paperback)

Zivot and Wang have done a phenomenal job of covering intermediate to advanced topics in econometrics along with the S programming language. Extensive literature reviews are coupled with robust examples and mathematics, and topped off with S code. I am a quantitative hedge fund manager, and I use the Open Source R package [..] and RMetrics [..]. I can adapt every single excercise in "Modeling Financial Time Series with S-PLUS" to use in R, and make use of them in my work. If I have one complaint it is that the book does not cover non-linear models like quantile regression or least squares, or optimization for much more than trivial two or three asset portfolios.

3 of 3 people found the following review helpful:

5.0 out of 5 stars Indispensible, October 26, 2008

By 

Scott C. Nelson (San Diego, CA) - See all my reviews
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This review is from: Modeling Financial Time Series with S-PLUS® (Paperback)

Just to be clear: buying this book does not mean you are buying S+Finmetrics. You need to purchase Splus base + the Finmetrics module separately. Unfortunately I tried to call SPLUS (twice) to obtain an academic license, and no one ever called me back. I ended up getting a copy from my university.

I wish SPLUS would set up an online download, where I can simply pay with a credit card and download the product immediately, instead of dealing with sales people. That's a very archaic distribution system in my opinion.

But this review is about this book. In fact, this book is AMAZING. It is basically a unique combination of a S+Finmetrics userguide and a primer on financial econometrics. It covers virtually all aspects of modern financial econometrics with an emphasis on practical examples. Theory is discussed to illustrate and motivate the examples. There are no proofs. If you want understand, say, a Vector Autoregression foreasting error decomposition, are you going to slog through Hamilton's "Time Series Analysis" and try to implement it on your own? No, you are going to turn to the nice tidy description in Ch11 of this book, and then call the "fevd" method, so you know what is doing and how to interpret the results.

A note on R vs. S+Finmetrics: much of the functionality in S+ Finmetrics is available in R, it's just spread across a lot of different packages. The advantage of a commercial product such as S+ Finmetrics is that it consolidates these packages, and provides (more or less) standardized methods and classes to support them.

For example, in R it is possible to fit a long memory ARIMA model using the function fracdiff. However in R the function fracdiff does not return residuals, the inclusion of exogenous x variables or support forecasting (no predict method). In SPLUS, the same function (FARIMA) returns all of these.