Introduction to Time Series and Forecasting [Hardcover]

Peter J. Brockwell (Author), Richard A. Davis (Author)

Book Description

Publication Date: March 8, 2002 | ISBN-10: 0387953515 | ISBN-13: 978-0387953519 | Edition: 2nd

This is an introduction to time series that emphasizes methods and analysis of data sets. The logic and tools of model-building for stationary and non-stationary time series are developed and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills. Statisticians and students will learn the latest methods in time series and forecasting, along with modern computational models and algorithms.

Editorial Reviews

Review

From the reviews: "The emphasis is on hands-on experience and the friendly software that accompanies the book serves the purpose admirably. ... The authors should be congratulated for making the subject accessible and fun to learn. The book is a pleasure to read and highly recommended. I regard it as the best introductory text in town." ISI Short Book Reviews

Product Details

• Hardcover: 456 pages
• Publisher: Springer; 2nd edition (March 8, 2002)
• Language: English
• ISBN-10: 0387953515
• ISBN-13: 978-0387953519
• Product Dimensions: 9.2 x 7.9 x 1.4 inches
• Shipping Weight: 2.4 pounds (View shipping rates and policies)
• Average Customer Review: 3.5 out of 5 stars  See all reviews (15 customer reviews)
• Amazon Best Sellers Rank: #69,698 in Books (See Top 100 in Books)

Customer Reviews

Most Helpful Customer Reviews

38 of 40 people found the following review helpful:

5.0 out of 5 stars Excellent introduction on time series analysis, January 31, 2001

By 

Steve Uhlig (Berlin, Germany) - See all my reviews
(REAL NAME)   

This review is from: An Introduction to Time Series and Forecasting (Springer Texts in Statistics) (Hardcover)

Very good introductory book to ARMA models. Full of real-life examples that provide some intuitive insight about the issues that may arise when modelling time series and forecasting. Requires some initial knowledge in statistics and algebra but if you're involved in time series modelling, it should be your first book.

29 of 30 people found the following review helpful:

5.0 out of 5 stars good modern cover of both time and frequency domains, January 22, 2008

By 

Michael R. Chernick "statman31147" (Holland PA) - See all my reviews
(REAL NAME)   

This review is from: Introduction to Time Series and Forecasting (Hardcover)

In contrast to their graduate text "Time Series: Theory and Methods" this book is more elementary and introductory and is pitched at the advanced undergraduate level requiring only calculus, elementary statistics and matrix algebra. It gives very good coverage to a wide variety of time series models and includes some nonstationary models. In this second edition the chapter on nonstationary models includes the latest coverage of ARCH and GARCH models presented in a way that I found very accessible.
Computations are done with ITSM and in this edition the ITSM 2000 version 7.0 edition is included on a CD so that students can reproduce the authors' calculations and run analyses of their own.

Another nice feature of the text that distinguishes it from other texts at this level is the introduction of multivariate time series, coverage of state space models, chaos and cointegration. Ideas are illustrated with examples. Important theory is discussed but is kept brief and theorems and proofs are not given to the extent of their other more theoretical text.

8 of 8 people found the following review helpful:

2.0 out of 5 stars Carelessly put together and VERY unorganized, September 17, 2010

By 

Young "grad student" (NY) - See all my reviews

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This review is from: Introduction to Time Series and Forecasting (Hardcover)

First off, my background is as follows: I have taken master's level courses in probability, statistical inference, linear regression, linear algebra, and differential equations from a very reputable university, and received high marks in all classes. Also, I've scored 800 on the Quantitative section of the GRE.

So you would think that a person like myself would find this book to be challenging yet rewarding and manageable. After spending 2 weeks trying to decipher the text, and going over 3 chapters, I've lost all hope in the book. When I read this textbook, it feels as though I am trying to understand the Authors' stream of consciousness.

As a student of math, I am quite used to spending countless hours deciphering the theorems and propositions of many mathematicians. But with this book, I also have the added burden of having to dicipher the Authors' thought process. To be clear, the material in the text book is very good, but the presentation of the material is that of a "rambler." At this point I have given up on the book as a source of my learning, and have purchased another text book to use as my reference.

I agree with the many other reviewers who stated that the book is unorganized and written poorly. It seems as though they spent MINIMAL time on producing this book just to meet a deadline. After the first few chapters, it REALLY gets annoying and makes you want to chastise the Authors for being so irresponsible. They may be geniuses in their field, but they have no right to teach the material with these kinds of products.

*UPDATE* 11DEC2010
I've more or less gone through the entire book(only by necessity since the homework questions were from the text). My opinion of this textbook still stands.
As an alternative I recommend "Analysis of Financial Time Series" by Tsay. I've read bits of it, and it seems very well written and progressive. Helped me out a TON in understanding ARCH/GARCH processes.