Book Description
Gain the statistical tools and techniques you need to understand today's financial markets with the Second Edition of this critically acclaimed book.
Youll find a comprehensive and systematic introduction to financial econometric models and their applications in modeling and predicting financial time series data. This edition continues to emphasize empirical financial data and focuses on real-world examples. Youll master key aspects of financial time series, including volatility modeling, neural network applications, market microstructure and high-frequency financial data, continuous-time models and Ito's Lemma, Value at Risk, multiple returns analysis, financial factor models, and econometric modeling via computation-intensive methods.
This is an ideal textbook for MBA students and a key reference for researchers and professionals in business and finance. Order your copy today.
Download Description
Analysis of Financial Time Series, Second Edition provides a comprehensive and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. The author begins with basic characteristics of financial time series data before covering three main topics: analysis and application of univariate financial time series; the return series of multiple assets; and Bayesian inference in finance methods.
Customer Reviews:
Excellent and detailed reference.......2007-05-03
The coverage of the topic is broad and deep. It is one of the few introductory books that devotes some space to transfer function modeling and does so intelligibly.
A must have for the novice as well as those more familiar with the topic that need a solid reference.
The best for Masters level, great all-around.......2007-02-12
This text is absolutely perfect for Masters students learning financial econometrics. There is a little theory, clear explanations, and quite a few real world examples. (I don't think any text would tell the reader what model to use when, because that's application-specific.) It assumes some knowledge of finance and basic econometrics/statistics, which is fair enough. To get more theory, Hamilton (1994) remains the authority, and Campbell, Lo, MacKinlay (1997) is a great introduction for PhD students, and generally an ideal companion volume to this one.
Excellent reference!.......2006-11-05
This book is an excellent toolbox for anyove dealing in the field of financial engineering, however, as a real toolbox, the author doesn't explain the exact use of all tools and how to interpret the results. This is why this book is for advanced users who need a well documented reference but it is not very suitable for beginners in the field. The Splus code is welcome.
Broad coverage, but not for the faint-hearted.......2006-07-05
Written by a University of Chicago professor, this book comprehensively covers times series topics relative to investment and trading-oriented finance (i.e., Wall Street money-making machines). Treatment is generally clear and thorough, but an advanced math and stat background is an absolute prerequisite for understanding the materials.
S-Plus/R code is given, but strangely, there is very little on *why* and
*when* one uses each of the techniques. Under what cirmcustances should I use or not use GARCH? What exactly is PCA good for in real-world applications? These important questions are not answered, in other words, you don't get a sense of the real-world context for these topics.
Best textbook I have ever read .......2005-09-19
First of all, it is well written in a very practical point of view. The whole book is aimed fullly to real financial data(appended in the author's web). People can gain not only the well-explained theories but the hand-on experience with data analysis using SPLUS or any other package.
Secondly, the author is a real expert in this field and has been publishing lots of nice work. All models in the book are clearly illustrated and commented.
Thirdly, it covers a lot of topics in analysis of FT. Reader can learn almost all the valuable things in this field from this book.
If anyone wanna truly learn this book, she/he has to sit down and plays some real data on computer. I think this is the best way and the only way to use this book.
Book Description
The last decade has brought dramatic changes in the way that researchers analyze economic and financial time series. This book synthesizes these recent advances and makes them accessible to first-year graduate students. James Hamilton provides the first adequate text-book treatments of important innovations such as vector autoregressions, generalized method of moments, the economic and statistical consequences of unit roots, time-varying variances, and nonlinear time series models. In addition, he presents basic tools for analyzing dynamic systems (including linear representations, autocovariance generating functions, spectral analysis, and the Kalman filter) in a way that integrates economic theory with the practical difficulties of analyzing and interpreting real-world data. Time Series Analysis fills an important need for a textbook that integrates economic theory, econometrics, and new results.
The book is intended to provide students and researchers with a self-contained survey of time series analysis. It starts from first principles and should be readily accessible to any beginning graduate student, while it is also intended to serve as a reference book for researchers.
Customer Reviews:
Excellent book in time series.......2007-06-29
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. .......2007-02-14
No complaints. I received the book before deadline and book is same as descrition. 100% recomended seller
Absolutely Excellent (for what it is).......2007-02-06
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.
Awesome book for TS.......2006-03-06
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.
A review of Time Series Analysis.......2005-08-05
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.
Average customer rating:
- modelling financial instruments
- good analysis on data error.
- From the experts in the field
- For the new millenium...that's what we need.
- More Than An Introduction
|
An Introduction to High-Frequency Finance
Ramazan Gençay ,
Michel Dacorogna ,
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Analysis of Financial Time Series, 2nd Edition (Wiley Series in Probability and Statistics)
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ASIN: 0122796713 |
Book Description
Liquid markets generate hundreds or thousands of ticks (the minimum change in price a security can have, either up or down) every business day. Data vendors such as Reuters transmit more than 275,000 prices per day for foreign exchange spot rates alone. Thus, high-frequency data can be a fundamental object of study, as traders make decisions by observing high-frequency or tick-by-tick data. Yet most studies published in financial literature deal with low frequency, regularly spaced data. For a variety of reasons, high-frequency data are becoming a way for understanding market microstructure. This book discusses the best mathematical models and tools for dealing with such vast amounts of data.
This book provides a framework for the analysis, modeling, and inference of high frequency financial time series. With particular emphasis on foreign exchange markets, as well as currency, interest rate, and bond futures markets, this unified view of high frequency time series methods investigates the price formation process and concludes by reviewing techniques for constructing systematic trading models for financial assets.
Customer Reviews:
modelling financial instruments.......2007-03-08
The book gives an indepth statistical modelling of important financial events, that have time dependency. It is suitable for the financial analyst who wants a semi-empirical approach.
For some quantities, like foreign exchange data, there is a comparison between fully empirical results and various theoretical models. What is investigated are such behaviours like scaling laws, for the absolute returns as a function of frequency. Here, it has been empirically observed that scalings do exist for FX rates.
Whenever possible, the book gives rigorous results, often encapsulated in theorems relating to distributions of independently distributed random variables. The reader should have a background in statistics, with the equivalent of several years of undergraduate courses.
good analysis on data error........2007-01-16
Many type of error the book list are frequently occur in FX data.
This book give good guide on how to filter them.
From the experts in the field.......2002-06-06
Michel Dacorogna and the team at the former Olsen & Associates are well-known experts in the field of foreign exchange rate data analysis, and their book provides us with a vast, useful source of information. Unfortunately for students and other beginners, the book is written like a compilation of papers and review articles, the opposite of pedagogical, and with an awful choice of 'computerese' notation (MA(t,n)=sum(EMA(t',k)... etc) that makes Boudhaud-Potters look easy in comparison. More to the point, even their noncomputerese notation is difficult to follow. I hope for a very different second edition written pedagogically for students of this growing and important field. On the positive side, data analyses are performed using logarithmic returns, not price increments. Workers in the field who consult this text will find it helpful.
For the new millenium...that's what we need........2001-07-23
The book covers a wide range of topics related to high-frequency data in Finance. There is a very detailed approach to tackle a huge amount of data and to deal with its based stylized facts. The book triggers the reader's desire to update his knowledge in the field of finance.
More Than An Introduction.......2001-05-28
This one of the few books on high frequency finance is a most welcome to the literature. The book is useful not only for people who are new to the subject but also for researchers in the field since it is a most uniform treatment of many topics. From adaptive data cleaning (chapter 4) to intraday and weekly seasonality (chapter 6) and real time trading models (chapter 11), it covers a broad range of topics specific to high frequency financial time series analysis. Chapters on volatility modeling (Chapter 8), forecasting (chapter 9) and correlation and multivariate risk (chapter 10) are enlightening especially for risk exposure analysis and risk management purposes. Finally, the the extensive bibliography is a precious source for those who would like to explore certain topics in detail. I highly recommend it for practitioners as well as researchers in the field.
Average customer rating:
|
Forecasting, Time Series, and Regression (with CD-ROM) (Forecasting, Time Series, & Regression)
Bruce L. Bowerman ,
Richard O'Connell , and
Anne Koehler
Manufacturer: Duxbury Press
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ASIN: 0534409776 |
Book Description
Awarded Outstanding Academic Book by CHOICE magazine in its first edition, FORECASTING, TIME SERIES, AND REGRESSION: AN APPLIED APPROACH illustrates the vital importance of forecasting and the various statistical techniques that can be used to produce them. With an emphasis on applications, this book provides both the conceptual development and practical motivation you need to effectively implement forecasts of your own. You'll understand why using forecasts to make intelligent decisions in marketing, finance, personnel management, production scheduling, process control, and strategic management is so vital.
Book Description
Deterministic chaos provides a novel framework for the analysis of irregular time series. Traditionally, nonperiodic signals are modeled by linear stochastic processes. But even very simple chaotic dynamical systems can exhibit strongly irregular time evolution without random inputs. Chaos theory offers completely new concepts and algorithms for time series analysis which can lead to a thorough understanding of the signal. The book introduces a broad choice of such concepts and methods, including phase space embeddings, nonlinear prediction and noise reduction, Lyapunov exponents, dimensions and entropies, as well as statistical tests for nonlinearity. Related topics like chaos control, wavelet analysis and pattern dynamics are also discussed. Applications range from high quality, strictly deterministic laboratory data to short, noisy sequences which typically occur in medicine, biology, geophysics or the social sciences. All material is discussed and illustrated using real experimental data.
Download Description
The paradigm of deterministic chaos has influenced thinking in many fields of science. Chaotic systems show rich and surprising mathematical structures. In the applied sciences, deterministic chaos provides a striking explanation for irregular behaviour and anomalies in systems which do not seem to be inherently stochastic. The most direct link between chaos theory and the real world is the analysis of time series from real systems in terms of nonlinear dynamics. Experimental technique and data analysis have seen such dramatic progress that, by now, most fundamental properties of nonlinear dynamical systems have been observed in the laboratory. Great efforts are being made to exploit ideas from chaos theory wherever the data displays more structure than can be captured by traditional methods. Problems of this kind are typical in biology and physiology but also in geophysics, economics, and many other sciences.
Customer Reviews:
Good for both beginners and advanced practitioners.......2003-10-22
In my search for good material on time series analysis, I have come across many books packed with information, yet so dry as to make them unreadable (readers of Hamilton's "Time Series Analysis" will know what I mean - Amazing book, but unreadably boring).
Kantz and Schreiber do not suffer from that all too common problem. They write clearly and in a very readable style. Their use of real-world datasets and numerous (though not overwhelming) charts makes their work quickly accessible even to beginniners in the field. They provide enough mathematical formalisms to make use of what they present, but not so many as to require a PhD in math to follow the flow of the text. For more advanced readers, they cover a wide range of topics useful both for analysis and for forecasting. Chapter 12, in particular, opened me to a whole world of new techniques.
As my one negative comment on this book, I would have liked that same chapter 12 fleshed out more, to the point that I would buy a follow-up book covering nothing but an elaboration on that single chapter.
If you have an interest in time series analysis and forecasting, and have grown tired of dry material that provides nothing more than yet another extension to ARIMA or Kalman filtering, you will love this book.
Excellent for practitioners.......2001-02-23
This book provides an excellent overview of chaos theory concepts applied to time series analysis. First part constitutes a good tutorial on chaos theory and its implications on time series analysis while the second part discusses in detail aspects of time-series related chaos theory concepts (with an historical perspective of the related research). Time series analysts will certainly benefit from it thanks to its balanced exposition of issues of chaos theory concepts for non-infinite data sets...
However, the only drawback is that it essentially deals with deterministic systems, not stochastic ones. But if you gathered your data on a physical system, it's OK.
Book Description
Time Series Analysis and Its Applications presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using non-trivial data illustrate solutions to problems such as evaluating pain perception experiments using magnetic resonance imaging or monitoring a nuclear test ban treaty. The book is designed to be useful as a text for graduate level students in the physical, biological and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels. Material from the earlier 1988 Prentice-Hall text Applied Statistical Time Series Analysis has been updated by adding modern developments involving categorical time sries analysis and the spectral envelope, multivariate spectral methods, long memory series, nonlinear models, longitudinal data analysis, resampling techniques, ARCH models, stochastic volatility, wavelets and Monte Carlo Markov chain integration methods. These add to a classical coverage of time series regression, univariate and multivariate ARIMA models, spectral analysis and state-space models. The book is complemented by ofering accessibility, via the World Wide Web, to the data and an exploratory time series analysis program ASTSA for Windows that can be downloaded as Freeware. Robert H. Shumway is Professor of Statistics at the University of California, Davis. He is a Fellow of the American Statistical Association and a member of the Inernational Statistical Institute. He won the 1986 American Statistical Association Award for Outstanding Statistical Application and the 1992 Communicable Diseases Center Statistics Award; both awards were for joint papers on time series applications. He is the author of a previous 1988 Prentice-Hall text on applied time series analysis and is currenlty a Departmental Editor for the Journal of Forecasting. David S. Stoffer is Professor of Statistics at the University of Pittsburgh. He has made seminal contributions to the analysis of categorical time series and won the 1989 American Statistical Association Award for Outstanding Statistical Application in a joint paper analyzing categorical time series arising in infant sleep-state cycling. He is currently an Associate Editor of the Journal of Forecasting and has served as an Associate Editor for the Journal fo the American Statistical Association.
Customer Reviews:
Not Reader-Friendly.......2007-09-27
As mentioned by some other reviewers, this book may be a good book in content, but it is very badly organized. The author references figures or equations from everywhere in the book. You have to go through chapters back and forth. Some important definitions are not clearly defined. They were just written into normal passages.
A good text book for Time Series and its computations.......2007-07-21
The book is very well designed; it covers most of the material for undergraduate course as well as some material for higher studies in TS analysis. It uses as vehicle for computations, which is very powerful and common as academic mathematical software, R.
I plan to use it as a text book in my course, which I teach at KS University.
Perfect for a Refrence after you've had a Time Series Class.......2007-06-13
While Enders remains the most popular book for those who are taking a time series class. I highly recommend this book as an advanced reference on the subject regardless of your research area. Shumway divides the book into basic, involved and finally advanced topics. He then subdivides these sections into time and frequency based time series. The result is a book that gives a very comprehensive review of all time series methods.
A greater plus for this book is that it introduces time series methods in R, and what packages one can use to perform time series analysis using the ever popular stats language. However, as an earlier reviewer has pointed out, the book does not go into a step by step walk through the packages, but rather gives enough information that a reader can easily look through CRAN to find more information on the exact workings of the packages and functions described within.
Over all, a must have for the bookshelf
Intermediate Applied Time Series book.......2007-05-13
Fist off, what this book is not: It is not a Time Series Theory book like Tsay or Brockwell. If all you want is mathematical rigor, go somewhere else.
Now, as to what the book is: it is an very easy to read intermediate text with examples drawn from the real world. It is also reasonably complete in building programming examples in R (with exception of Chapter 7, lamentably ... Chapter 6 code is available on the book's website).
One other reviewer commented that some of the examples consist of only one line of R code. This is part of the power of R and CRAN that such powerful statistical techniques like ARIMA and Factor Modeling can be represented in a single function call, and not a shortcoming of the book.
This book will not replace Tsay or Zivot and Wang on my shelf, but is an accesible, excellent text that does a very good job of covering its intended purpose, including some relatively advanced topics. Publishing code for Chapter 7 would rate this book its fifth star.
A review from someone who has actually read the book.......2007-02-20
As the title implies, the book is a text on time series analysis and its applications. It is a modern treatment of time series analysis with a slant toward applications. The applications are interesting and involve current topics such as global warming. The examples are broad in range, including data from various fields such as biology, economics, engineering, environmental science, and medicine. The book is interesting and accessible, and it provides an excellent introduction various aspects of the analysis of time series. The text covers both the spectral and time domains, including a thorough presentation of state-space models. The basic requirement for being able to understand most of the text is knowing the material that would be covered in introductory courses on regression and mathematical statistics.
The book has many interesting and "real" (as opposed to "toy") examples and, as the subtitle explains, many of the examples have associated R code. This makes for a positive experience because you can replicate the analyses. Accordingly, there is no guessing as to what was done to obtain the results of an example. It is completely wrong to say that "R is not relevant". But you do not have to take my word for it! Just go to the website for the text at StatLib and all the R code in the text is posted there. In addition, as the authors' state in the Preface (which is also available for viewing at the website for the text), R code for the state-space chapter (Chapter 6) is on the website for the text. There you will find code for the Kalman filter and smoothing algorithms, as well as the EM algorithm and some examples for maximum likelihood estimation. The website for the text also has a small tutorial for a quick start on using R to do time series analysis. The tutorial is great for a beginner.
At the end of the day, the text is not an R manual. It never says it is and I do not understand why anyone would think it should be an R manual. It is also not a manual for making wine and it will not help you train your dog. It is, however, an accessible modern introduction to time series analysis with many interesting examples that have associated R code. And, while you are learning time series analysis, you will also learn how to use R for analyzing time series.
Book Description
This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied in economics, engineering, and the natural and social sciences. The book assumes knowledge only of basic calculus, matrix algebra and elementary statistics. This second edition contains detailed instructions on the use of the new totally windows-based computer package ITSM2000, the student version of which is included with the text. Expanded treatments are also given of several topics treated only briefly in the first edition. These include regression with time series errors, which plays an important role in forecasting and inference, and ARCH and GARCH models, which are widely used for the modeling of financial time series. These models can be fitted using the new version of ITSM. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include the Burg and Hannan-Rissanen algorithms, unit roots, the EM algorithm, structural models, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introductions are also given to cointegration and to non-linear, continuous-time and long-memory models.
Customer Reviews:
good basic intro.......2006-11-10
A decent basic introduction covering a lot of topics. It's much more accessible for learning the subject for the first time then many other books which pile on the mathematical notation and obscure the actual meaning of things. The accompanying CD is very nice, although it gets annoying very fast that you're restricted to very small dataset sizes---but it does help in learning. The only two things that are somewhat of a problem with this book are 1) many times, rather than clearly stating "here's the algorithm you need to implement", you are referred to 3 or 4 other sections of the book for pieces of the algorithm, often without a clear explanation of exactly how that earlier section is supposed to be worked into the current desired algorithm and 2) there aren't a lot of practical insights as to how to actually initialize many of the algorithms (everything is great if you already know all the parameters in advance but starting from scratch with just raw data isn't dealt with I think as fully as would be useful). All in all, though, the book is helpful and, as I said, very good for learning the essential concepts for the first time.
When is an Introduction not an Introduction?.......2006-11-05
In the process of building a website targeted to those good folks that are striving valiantly to make a living through Internet marketing, you might think that an early objective would be to assemble a library of good reference material. After all, if you are planning on providing sensible information to your readers, then you should have a few good text books on hand to refer to when you need to be sure that some little tidbit of information might actually work. Well, at least I did. So, I have been scouring the Internet for textbook on the subject of Forecasting, which we share a common interest in. I have purchased a few and, for the most part, they are really quite informative and will be useful when the time comes. There is, however, an exception to this.
One book I purchased bears the title "Introduction to Time Series and Forecasting, Brockwell, Peter J and Richard A Davis". Being an intelligent sort of chap, I naturally took the word "Introduction" to mean just that. You know, you've been introduced to people before and becoming introduced usually means that 1. You look at the face. 2. You grasp their hand and shake firmly and 3. You exchange pleasantries, such as "Hello, it's nice to meet you".
Now, I never blame the person making the introduction if the relationship doesn't work out. After all, it's not their fault that two people hopefully sharing a common interest (after all, why bother making an introduction?) aren't all that compatible. There are likely to be many reasons for the incompatibility, the first of which could be that people travel in different circles and your circle isn't ever going to be part of their circle. Sort of an exclusionary relationship, you might say. And, not to be overly judgmental of others, of course, there may be plenty of good reasons for that. If everyone existed in one social circle, after all, the world would be beyond boring.
Anyways, the text book is a wonderful creation, that is, if you're a post-graduate or doctoral candidate. Upon opening the cover, expecting to be warmly introduced, I was rather amazed at the depth of equations and formulas gracing practically every page. I felt intimidated immediately. Remember the movie "The Ring"? This had to be rocket science, or more correctly, forecasting science at its most extreme! Wow! I should have really paid more attention during my statistics classes. So, I quickly closed the cover and tried to get a refund from the seller. Note the word Tried here. They didn't want it back either.
The good Post-Grand and PhD. candidates of the science of forecasting probably don't need an "Introduction" to Time Series and Forecasting. Next time I buy a book, I think I'll look for something with "Sandbox" in the title.
May all your Forecasts be Good Forecasts at [...]
Awesome.......2006-08-04
this book is excellent because it provides us with many examples and detailed explanations.
Not sure if it is introductory.......2005-12-24
I think the book is not written in a very organized way. It's not a book for picking up time series quickly. It's saturated with information, which I'm not sure if it's necessary for implementation. I have no problem following the math, however, if I want to pick up something and implement it within a day or two, the book is a bit harder to digest. Wouldn't think this is an undergraduate course book as it covers convergence in probability or mean-squared, which I learnt in PhD courses, not even master level.
Great book for a great price.......2004-02-12
This is one of those books that you can't find much cons to it. The book is inexpensive, and it's unbelievably lightweight. The material is rich, and yet easy to understand. The author actually brings you step by step from elementary to theorectical proofs.
Book Description
* Contains additional discussion and examples on left truncation as well as material on more general censoring and truncation patterns.
* Introduces the martingale and counting process formulation swil lbe in a new chapter.
* Develops multivariate failure time data in a separate chapter and extends the material on Markov and semi Markov formulations.
* Presents new examples and applications of data analysis.
Customer Reviews:
A welcome and well-written update to a classic in the field. .......2005-08-25
The prior edition of this book has long been used for introductory courses in survival analysis for statistics students, and its treatment of the proportional hazards model and partial likelihood is classic. Contrary to the claims of another reviewer here, notation for the survival function is far from standardized in the field. In fact, both this book and another standard text ("Analysis of Survival Data" by D.R. Cox and D. Oakes) represent this quantity with an "F". An excellent and authoratative introduction for students with some knowledge of theoretical statistics.
Average customer rating:
- Excellent reference
- Good intro and review of the material
- Excellent as a practical quide - a must have handbook - recent development are here too
- Practical book on time series econometrics
- An Elementary Book
|
Applied Econometric Time Series, 2nd Edition
Walter Enders
Manufacturer: Wiley
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Similar Items:
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Time Series Analysis
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Analysis of Panel Data
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Econometrics
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Econometric Analysis (5th Edition)
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Analysis of Financial Time Series, 2nd Edition (Wiley Series in Probability and Statistics)
ASIN: 0471230650 |
Book Description
Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. The first edition of Applied Econometric Time Series was among those chosen.
This new edition reflects recent advances in time-series econometrics, such as out-of-sample forecasting techniques, non-linear time-series models, Monte Carlo analysis, and bootstrapping. Numerous examples from fields ranging from agricultural economics to transnational terrorism illustrate various techniques.
Customer Reviews:
Excellent reference.......2007-09-18
This book is an excellent reference guide and a must have book to everyone interested in time series analysis.
Good intro and review of the material.......2006-03-09
Having read a few books on time series analysis, Enders provides the best introduction to the area. The approach is simple and practically oriented. Explaining the basics of the area with limited use of math is beneficial. With this area developing so rapidly, a new, updated edition would be a welcome book on my shelf.
Excellent as a practical quide - a must have handbook - recent development are here too .......2006-02-04
I bought this book as an introductory reading to time series. And found it very easy to understand, both the theoretical explanations and practical applications. I think it is a "must have handbook" for any economics student. The last edition also covers the recent panel unit root tests, not the 2nd generation ones but Im, Pesaran, Shin panel test is explanained pretty well. Graphical illustrations of series and visual detection of possible problems are nice for beginners. Also, shows how to analyze data step-by-step with plenty of examples. In overall I think it is a great investment for those doing empirical studies and/or starting to learn/work with time series.
Practical book on time series econometrics.......2005-03-29
I am a Financial Engineer working primarily in risk management. Over the past few months I've had to study up on time series-related topics (both GARCH and cointegration-based analyses). This book is excellent for someone who needs to find time-series information and then apply it to a problem in a hurry. The explanations are clear and intuitive, yet mathematically precise. There are plenty of examples on how to apply techniques to real world problems, including lucid discussions of the proper statistical tests to use for the various methodologies.
Like many engineers, I often find myself scrambling to find a good source for a model or system component I will have to design, usually under tight time constraints. This is a perfect example of the type of textbook I always hope to find when starting such a task.
An Elementary Book.......2001-05-20
The book is an introduction to time series and covers ARMA, VAR Unit roots and Basic Cointegration, is a good book for people that want learn time series quickly, the book has some elementary theory of time series and many examples and exercises, the computacional problems needs some of RATS ...the book describes time series without advanced mathematics.
Book Description
Since 1975, The Analysis of Time Series: An Introduction has introduced legions of statistics students and researchers to the theory and practice of time series analysis. With each successive edition, best-selling author Chris Chatfield has honed and refined his presentation, updated the material to reflect advances in the field, and presented interesting new data sets. The sixth edition is no exception. It provides an accessible, comprehensive introduction to the theory and practice of time series analysis. The treatment covers a wide range of topics, including ARIMA probability models, forecasting methods, spectral analysis, linear systems, state-space models, and the Kalman filter. It also addresses nonlinear, multivariate, and long-memory models. The author has carefully updated each chapter, added new discussions, incorporated new datasets, and made those datasets available for download from www.crcpress.com/e_products/downloads/. Highlights of the Sixth Edition: · A new section on Handling Real Data · New discussion on prediction intervals · A completely revised and restructured chapter on more advanced topics, with new material on the aggregation of time series, analyzing time series in finance, and discrete-valued time series · A new chapter of Examples and Practical Advice · Thorough updates and revisions throughout the text that reflect recent developments and dramatic changes in computing practices over the last few years The analysis of time series can be a difficult topic, but as this book has demonstrated for two-and-a-half decades, it does not have to be daunting. The accessibility, polished presentation, and broad coverage of The Analysis of Time Series make it simply the best introduction to the subject available.
Customer Reviews:
introduction rather than explanation.......2007-09-07
This book should be considered as "only and pure" introduction to the subject. It suffers from the basic problem of social science oriented writing in mathematical issues: while trying to keep out "complicated details" it mystifies and obscures the subject and leaves out a lot of interesting topics. It would have been better to find ways to explain mathematical theory behind the concepts rather than frightening the readers by describing some issues as "deep waters". However, to be fair it is essential to say that the book with its concise manner and modest ambition still deserves some credit
Too basic but complex.......2007-07-05
It is amazing how complex is this book without the requiered formality for the field. As a very first approach, could be useful, but definitly, Tsai book is better.
Excellent introduction to time series........2005-07-29
I have read the entire book, and I am quite satisfied with it. I think it is an excellent introduction for anyone with the requisite background in calculus, probability, and statistics.
Excellent starting place for time series analysis.......2002-11-02
This tidy book is a highly readable, introductory survey to the topic of modern time series analysis. It excels in its ability to focus on the more intuitive aspects of analysis and model identification. The discussion of both time- and frequency-domain approaches is reasonably balanced, and Kalman filtering is also introduced. While it touches on many modern aspects of time series analysis, it sometimes (intentionally) lacks important technical depth necessary for implementation.
The author has done an admirable job at keeping the book manageably small. However, the reader is occasionally left wanting where interesting details are omitted because the author considered them "beyond the scope" of the book. For example, the preface mentions that several new topics are incorporated into the 5th edition (wavelets, for example), but the reader only finds a gratuitous single paragraph with references to complementary journal articles. In these few rare cases, the discussions are not intuitive enough for the reader to know whether it would be profitable to bother with further research at the professional journal level. Still, this title does well to reference the most important landmark works in the time series literature. Those performing remedial research may find it is easier - and more productive - to simply consult Chatfield's recommendations of important topical works before resorting to online or library literature searches.
This text has been in print since 1975 with new editions arriving every 5 years or so (perhaps even a 6th edition is close, since the last edition is copyrighted 1996). I am usually suspicious of textbooks having increasingly larger numbers of editions because the continual re-writing implies some level of recurring insufficiency. However, the frequency of update is probably justified due to continuing advances in this field of study. As a result, this title is surprisingly current given its introductory status (although the 4th and 5th editions do not differ too much).
For someone new to time series analysis, this may be one of the better places to start, especially for the price. Readers lacking in intuition or experience in time series analysis - especially non-statisticians - will certainly appreciate this introductory title. The more experienced analyst will also be well served by the author's expert perspectives - but to do practical work, this text will still likely need to be supplemented. The generous citation of additional literature will help the reader to know where to go next.
concise and well written introduction to time series.......2001-04-19
When I was a graduate student at Stanford my advisor taught an elementary time series course out of Chatfield's book. It was either the first or the second edition. I was his teaching assistant. The book has been very successful and is now in its fifth edition. It covers most of the important topics concisely and in an intuitive manner. This book gives the student a feel for time series analysis and an appreciation for its applicability. It is not meant for someone who wants a rigorous treatment and a strong understanding of the theory. For that the text of Brockwell and Davis or Anderson or Brillinger or Priestley are more appropriate.
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