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This book represents an integration of theory, methods, and examples using the S PLUS statistical modeling language and the S FinMetrics module to facilitate the practice of financial econometrics It is the first book to show the power of S PLUS for the analysis of time series data It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance Readers are assumed to have a basic knowledge of S PLUS and a solid grounding in basic statistics and time series concepts This edition covers S FinMetrics 2.0 and includes new chapters....

Title : Modeling Financial Time Series with S-PLUS®
Author :
Rating :
ISBN : 0387279652
Format Type : Paperback
Language : English
Publisher : Springer 2nd edition August 3, 2006
Number of Pages : 998 pages
File Size : 676 KB
Status : Available For Download
Last checked : 21 Minutes ago!

Modeling Financial Time Series with S-PLUS® Reviews

  • B. Peterson
    2019-04-16 22:19

    Zivot and Wang have done a phenomenal job of covering intermediate to advanced topics in econometrics along with the S programming language. Extensive literature reviews are coupled with robust examples and mathematics, and topped off with S code. I am a quantitative hedge fund manager, and I use the Open Source R package [..] and RMetrics [..]. I can adapt every single excercise in "Modeling Financial Time Series with S-PLUS" to use in R, and make use of them in my work. If I have one complaint it is that the book does not cover non-linear models like quantile regression or least squares, or optimization for much more than trivial two or three asset portfolios.

  • Scott C. Nelson
    2019-04-09 17:11

    Just to be clear: buying this book does not mean you are buying S+Finmetrics. You need to purchase Splus base + the Finmetrics module separately. Unfortunately I tried to call SPLUS (twice) to obtain an academic license, and no one ever called me back. I ended up getting a copy from my university.

  • N. Tuzov
    2019-04-11 21:12

    I'd like to do some comparative analysis here: Matlab's GARCH Toolbox has GARCH, GJR(TGARCH), EGARCH specifications for the volatility term. A single (out of many more) procedure "garch" in S+Finmetrics has that plus PGARCH and three GARCH-M options. Given how expensive Matlab GARCH Toolbox is, none could hope to get a more advanced S+Finmetrics pack for $57. I guess the people who expected otherwise knew nothing about SPLUS and wrongly assumed that "base" SPLUS is the econometric package in question.

  • Amazon Customer
    2019-04-03 15:11

    This is an excellent book on financial econometrics, very practical yet rigorous. I wish all econometrics/statistics textbook could like this. Basic theory followed by practical examples - real life examples, not simplified ones like in other books. The authors gave detailed instructions on how to implement various econometric models, i.e. multi-factor models, GARCH, MGARCH, long memory models, state-space, etc. Most econometrics textbooks are at two extremes, they are either too theoretical (you still don't know how to put those models in real life), or too simple (lack of mathematical rigor and without advanced applications). This book is a combination of both worlds, computer codes/math models, and real life examples (some really good ones). A lot of cutting-edge techniques and advanced topics are also covered.

  • LUKE O.
    2019-03-26 14:17

    The best thing about this book is that it combines financial time series analysis with "real-life" examples that are either reproducible or easily adaptable. Being that it is also the user manual for the S+FinMetrics module for the SPLUS stats. package it also reads like a software manual (some people like that). This book provides a good sample of many time series techniques that can be applied out of the box.

  • Another Disappointed Reader
    2019-04-12 19:54

    As other reviewers have mentioned, this book is useless without FinMetrics. It is merely a user manual for that package, and has hardly any intrinsic value on its own.