Analysis of Financial Time Series (text only) 2nd(Second) by R. S. Tsay

by Ruey S. Tsay

Analysis of Financial Time Series (Wiley Series in Probability and Statistics) [Hardcover] Ruey S. Tsay (Author)

Genres: Finance, Economics, Mathematics, Textbooks, Science, Reference, Social Science

Hardcover

First published October 15, 2001

Reviews

[Dmitri · Rating 5 out of 5]

Even though the liars and cheats have poisoned the well by trying to convince everyone that Technical Analysis is a viable scientific discipline (it's not), Time Series Analysis is a different, more scientifically rigorous and realistic approach to understanding different effects, if there are any, in financial time series. This book provides comprehensive coverage of the current state of the art, including plenty of R examples. Of course, unlike those books that promise to teach housewives the art of FX trading in just a week or two, this book requires a background in mathematical statistics - a typical first-year university course should have you covered (see Probability and Statistics for a good book to take you there).

[Max Lybbert · Rating 3 out of 5]

Tsay provides a very extensive tour of modern financial analysis. The book discusses various models (AR, MA, ARMA, ARIMA, GARCH, etc.), but I found the discussion somewhat uneven: in some cases, Tsay provides large amounts of context and points to specific strengths or limitations, but in others he lets the equation speak for itself. Since the book is described as targeted at "introductory courses on time series at the graduate level," I can't fault this approach, but I'm sure I didn't always get the finer points when Tsay didn't call those points out.

References to Tsay's earlier work appears throughout, but if he has made contributions -- and it looks like he has -- then he is entitled to cite his earlier work. I am happier with this book that I was with Risk and Asset Allocation. Springer Finance., but it's certainly not an easy read.

[David · Rating 4 out of 5]

Excellent introduction to not only time series but also contains good information on stochastic calculus and statistical concepts. The author is adept at communicating the ideas and the mathematics clearly and logically. I'm looking forward to trying out the R programs included in the book.

[Terran M · Rating 5 out of 5]

This is a very clear and well-written coverage of many aspects of time series. Even if you're not particular interested in finance, it's still a great book; the majority of it is not specific to finance at all. It's not easy, but I think it's as easy as it can possibly be given the concepts being expained. The author is a very good writer.

Note that the examples are given in a wide variety of tools, and some techniques are demonstrated in only one tool, which may not be the one that you like to use. So don't read this book primarily for the code examples.

[Duncan McKinnon · Rating 3 out of 5]

This is a dense and highly technical textbook. As someone who generally enjoys knowing the detailed mathematics behind the models, I found this book hard to get through. That's not to say it doesn't provide a wealth of very useful information, but each page is packed with details that often form the pre-requisites for later explanation. It is not a linear read, but if you have the motivation to read and re-read each page, you will undoubtedly come away with a strong grasp of financial time series analysis.

[Daniel Siliski · Rating 1 out of 5]

Not practical. Read it cover to cover, kept it on my desk for 5 years, never once pulled it down to reference anything of value for my job (as a HF quant and risk manager.) Basically its a catalogue of what you'd learn as an undergraduate econometrician, with no useful purpose for real researchers or investors.