Its an excellent book to study advanced time series and for theoretical understanding of Time series. A must read at the graduate level.

Thanks Mr. Hamilton for writing such an excellent book

The best textbook I know for time series analysis. almost any topic is found . Negative point is the explanation is not very friendly. misses some topic like quasi-maximum likelihood estimation. only a few pages have it without any depth.

This is a large text in time series analysis that is designed for graduate students as the author acknowledges in his preface. It deals primarily with the theory and the tools rather than providing practical applications. It does not require a Ph.D. but does require a fair amount of mathematical sophistication that comes from advanced courses in probability and statistics. There are many good books at this level. This one has some unique features. It covers the traditional ARIMA models that can be found in most texts and uses the operator notation that Box and Jenkins introduced. It adds vector autoregressions which is fairly recent material. Spectral analysis (the frequency domain approach)is also covered and asymptotic theory is presented. Linear systems (more common to econometric time series than in the standard statistical books) is covered. Topics not commonly covered in competitor texts include nonstationary cases (both univariate and multivariate)with unit roots to the characteristic equation, Bayesian approaches, heteroscedastic models including the ARCH models and the topic of cointegration originally developed by Clive Granger. The book is loaded with references to the literature and is slanted towards methods useful in econometrics. Other good books at this level include Brockwell and Davis (1987), Fuller (1976), Anderson (1971), Harvey (1981) and Shumway and Stoffer (2000). Good texts solely in the frequency domain include Bloomfeld (1976), Priestley (1981), Koopmans (1974) and Brillinger (1981). Box, Jenkins and Reinsel (1994) provides practical applications using the Box-Jenkins time domain approach.

I purchased "Time Series Analysis" after reading that this was the time series "Bible". This book is certainly as long as a Bible, yet, paradoxically, it doesn't seem to contain very much useful information. Every time I look something up in it, its not there.

This book is almost 800 pages long and contains chapters on all of the main areas of time series analysis, including stationary ARMA models, VAR models, ARCH models, cointegration, etc. Hamilton gives all of the relevant proofs and algebra relating to these areas. However, he provides no worked examples to illustrate these concepts, which makes them very difficult to absorb. Hamilton provides some exercises at the end of each chapter (with solutions at the end of the book), but not enough to develop a working knowledge of this material.

I purchased this book because I needed to fit time series models as part of my PhD thesis and because I teach a unit on time series analysis to final-year undergraduate students. I have found this book completely useless for both of these purposes. At the same time I purchased this book, I also purchased Time Series Analysis and Its Applications: With R Examples (Springer Texts in Statistics) and Econometric Analysis (5th Edition) and I have found both of these books to be infinitely more helpful.

I don't think there is another book out ther that would outperform this book in time series econometrics. A must have if you are a graduate student in economics.

No complaints. I received the book before deadline and book is same as descrition. 100% recomended seller

Hamilton is often dubbed, "too hard to understand." That may be true, but actually it seems to be much more reasonable and readable than other econometrics texts I have attempted to read.

I would definitely not start out into econometrics with this book though. You probably will not be able to appreciate how good this book is until you have tried to read something as atrocious as Greene.

As is typical with almost every upper level econometrics book, it assumes you have a wide mathematical and statistical knowledge base that you may or may not have. I would not recommend it as a beginning graduate econometrics book but it is a great reintroduction to time series methods. I will say that I haven't found a single book yet in intermediate econometrics that I felt was written clearly or concisely.

Still, overall, this has been by far the best among the worst and I would highly recommend reading it to anyone who is beginning to study time series econometrics in some detail.

If you are thinking of mastering TS this is the book to start with. Do not get intimidated however with all the symbols and notations, the author does a pretty good job explaining each and every equation. A seperate book is needed for application eg RATs handbook by Enders.

The book provides a good overview of the analysis of time series and it also gives a good treatise of the economitric background of the use of estimation methods.

As you may guess from the title, I loved Hamilton's book. I must definitely disagree with all those who find it too technical. Rather on the contrary, I would say. Admittedly, entire pages with greek letters look intimidating at first glance. But what Hamilton actually does is making a huge effort (unlike most of his competitors) to actually explain the details of the derivations, thereby helping the reader a lot. You'll learn to appreciate this a lot by the time you start developing sth. on your own rather than simply applying existing techniques.

By now, I've been through most of the chapters and I'm yet to find a typo, let alone a major mistake. Whenever I wanted to learn sth. about Time Series Analysis, Hamilton provided a good starting point, if not more.

I am waiting for the second edition!