Good references for time series? I am wondering if anyone has book references for time series. I would like something comparable (in popularity) to the 'ESL' or to 'Machine learning' from Murphy in the machine learning field. 
Does anyone knows what are the most complete (in term of methods scope) books containing all about exponential smoothing (all of them), arima, sarima , arch, garch, neural network for time series, kalman filters, ... etc ? 
 A: I don't know of a single time series book that is as comprehensive as Elements of Statistical Learning. However, here's a list of a few books that i've found helpful:
Free online. More of a forecasting focus, but definitely a good starting point. The slides under resources are also helpful:


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*Hyndman, R. J., & Athanasopoulos, G. (2013). Forecasting: principles and practice. Retrieved from http://otexts.org/fpp/
Probably the most comprehensive. With information about many of the model types you've listed: 


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*Shumway, R. H., & Stoffer, D. S. (2010). Time Series Analysis and Its Applications. Springer.


Definitive resource on exponential smoothing:


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*Hyndman, R., Koehler, A. B., Ord, J. K., & Snyder, R. D. (2008). Forecasting with Exponential Smoothing. Springer.

A: Brockwell and Davis wrote two excellent time series books. Both cover a great deal of material and the writing is very clear. The first book is more introductory, and the second one has a more mathematical development. 
http://www.amazon.com/Introduction-Forecasting-Springer-Texts-Statistics/dp/0387953515/
http://www.amazon.com/Time-Series-Methods-Springer-Statistics/dp/1441903194
A: I don't know about the 'ESL' or machine learning, but what about good ol' Tsay?
Some parts you mentioned are included, some not (e.g. Kalman filter):

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*Analysis of Financial Time Series by Ruey S. Tsay
When it comes to times series with applications and an easy-to-understand way of explaining he is my Tom Cruise, my top gun.
A: ESL is not for time series in my opinion. Tsay's book in addition to Cowpertwait's intro level book are the best combination. 
A: Have a look at 


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*James D. Hamilton. Time Series Analysis. Princeton Univ. Press, Princeton, N.J, 1994.


It is very thorough. I'm not sure about neural networks and "all" exponential smoothing, but the rest is in there. 
A: Here is a good list of books on time series analysis. Note that there is a lot of difference amongst books that cater to people of different backgrounds (economists/engineers/statisticians). hth
