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I started by Time Series Analysis by Hamilton, but I am lost hopelessly. This book is really too theoretical for me to learn by myself.

Does anybody have a recommendation for a textbook on time series analysis that's suitable for self-study?

Thank you so much!

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I think should be a community wiki question. –  Rob Hyndman Jan 3 '12 at 8:41
@RobHyndman: Hi Rob. Thanks for your reply. How do I start a community wiki question, though? –  CodeNoob Jan 3 '12 at 13:53
@CodeNoob (Simply flag your question for moderator attention and we'll convert it to CW for you.) –  chl Jan 4 '12 at 8:05
Could you provide a little bit more details on what are your particular needs: academic (scientific, PhD), practical (model building, engineering, programming), level of disaggregation (macro, micro, panel data), field of application (microeconomics, macroeconomics, finance, physical sciences), may be some other details you feel are relevant. –  Dmitrij Celov Jan 4 '12 at 12:20
@DmitrijCelov Hi Dmitrij, I just need some basic time series introductory text, kind of general. But I will apply it to financial and econometric data analysis though –  CodeNoob Jan 6 '12 at 17:09

10 Answers 10

up vote 10 down vote accepted

I would recommed the following books:

  1. Time Series Analysis and Its Applications: With R Examples
  2. Time Series Analysis and Forecasting by Example

I hope it helps you. Best of luck!

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(+1) I've found the first book you listed there to be very useful. –  Macro Jan 3 '12 at 3:19
Biostat, could you clarify WHY you would recommend those books, above others? –  naught101 Mar 7 '12 at 0:01
or you, @Macro, considering this is a community wiki? –  naught101 Mar 27 '12 at 0:49

It depends on how much math you want. For a less mathematically-intense treatment, Applied Econometric Time Series by Enders is well-regarded.

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In addition to the other text there are two books introductory books in Springer's Use R! series that cover time series:
Introductory Time Series with R and Applied Econometrics in R

There is also an advanced econometrics text in the series, Analysis of Integrated and Co-integrated Time Series with R.

I have not used these but have found several others in the series to be excellent.

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Part Four of Damodar Gujarati and Dawn Porter's Basic Econometrics (5th ed) contains five chapters on time-series econometrics - a very popular book! It contains lots of exercises, regression outputs, interpretations, and best of all, you can download the data from the book's website and replicate the results for yourself. Another good book is Stock and Watson's Introduction to Econometrics.

Starting with Hamilton was admirable, but I'd say read through both of the time-series sections in the two books that I just mentioned and then move on to something like Walter Enders' Applied Econometric Time Series or Terrence C Mill's The Modelling of Financial Time Series.

After this (and probably after some review of mathematical economics) then you should be able to sit down and read Hamilton comfortably.

Note: Box & Jenkins' 1970 classic Time series analysis: Forecasting and control is obviously more concentrated (i.e. narrower in content) than the "modern textbooks" that I mentioned, but I'd say that anyone who wants to get a real good understanding of time-series shouldn't leave this off their reading list.

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Forecasting: principles and practice by Rob J Hyndman and George Athanasopoulos is available free online: http://otexts.com/fpp/

It's a good book in its own right; Hyndman's previous forecasting book with Makridakis and Wheelright is highly regarded, but this has the added advantage that you can see what you're getting for the price.

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We're looking for long answers that provide some explanation and context. Don't just give a one-line answer; explain why your answer is right, ideally with citations. Answers that don't include explanations may be removed.

There are some good, free, online resources:

  1. The Little Book of R for Time Series, by Avril Coghlan (also available in print, reasonably cheap) - I haven't read through this all, but it looks like it's well written, has some good examples, and starts basically from scratch (ie. easy to get into).
  2. Chapter 15, Statistics with R, by Vincent Zoonekynd - Decent intro, but probably slightly more advanced. I find that there's too much (poorly commented) code, and not enough explanation thereof.
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There are a few books that might be useful. If you are mathematically challenged you might want to start with two SAGE books by Mcdowall, Mcleary, Meidinger and Hay called "Interrupted Time Series Analysis" 1980 OR "Applied Time Series Analysis" by Richard McLeary. As you learn more about time series and decide that you you want more than prose and that you are willing to suffer through some math the Wei text published by Addison-Wessley entitled "Time Series Analysis" would be an excellent choice. In terms of web-based educational material, I have written a lot of useful material which can be viewed at http://www.autobox.com/AFSUniversity/afsuFrameset.htm entitled "Introduction to Forecasting".

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The autobox link seems to be broken. Is there a mirror? –  AK. May 23 '12 at 23:36

If you use Stata, Introduction to Time Series Using Stata by Sean Becketti is a solid gentle introduction, with many examples and an emphasis on intuition over theory. I think this book would complement Ender rather well.

The book opens with an intro to Stata language, followed by a quick review of regression and hypothesis testing.

The time series part starts with moving-average and Holt–Winters techniques to smooth and forecast the data. The next section focuses on using these for techniques forecasting. These methods are often neglected, but they work rather well for automated forecasting and are easy to explain. Becketti explains when they will work and when they won't.

The next chapters cover single-equation time-series models like autocorrelated disturbances, ARIMA, and ARCH/GARCH modeling.

In the end, Becketti discusses multiple-equation models, particularly VARs and VECs, and non-stationary time series.

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There's the NBER Summer Institute "What's New in Time Series Econometrics" (not sure whether this material is gated or not). There are videos with accompanying slides. The lectures are given by a pair of professors (Stock and Watson) who are known for their popular undergraduate econometrics textbook.

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We're looking for long answers that provide some explanation and context. Don't just give a one-line answer; explain why your answer is right, ideally with citations. Answers that don't include explanations may be removed.

A good collection of books is listed here. Some on the list are great for self starters. hth

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