Multiple Time Series Modeling Using the SAS VARMAX Procedure

Nonfiction, Science & Nature, Mathematics, Statistics, Computers, Application Software
Cover of the book Multiple Time Series Modeling Using the SAS VARMAX Procedure by Anders Milhoj, SAS Institute
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Anders Milhoj ISBN: 9781629597478
Publisher: SAS Institute Publication: January 11, 2016
Imprint: SAS Institute Language: English
Author: Anders Milhoj
ISBN: 9781629597478
Publisher: SAS Institute
Publication: January 11, 2016
Imprint: SAS Institute
Language: English

Aimed at econometricians who have completed at least one course in time series modeling, Multiple Time Series Modeling Using the SAS VARMAX Procedure will teach you the time series analytical possibilities that SAS offers today. Estimations of model parameters are now performed in a split second. For this reason, working through the identifications phase to find the correct model is unnecessary. Instead, several competing models can be estimated, and their fit can be compared instantaneously. Consequently, for time series analysis, most of the Box and Jenkins analysis process for univariate series is now obsolete. The former days of looking at cross-correlations and pre-whitening are over, because distributed lag models are easily fitted by an automatic lag identification method. The same goes for bivariate and even multivariate models, for which PROC VARMAX models are automatically fitted. For these models, other interesting variations arise: Subjects like Granger causality testing, feedback, equilibrium, cointegration, and error correction are easily addressed by PROC VARMAX. One problem with multivariate modeling is that it includes many parameters, making parameterizations unstable. This instability can be compensated for by application of Bayesian methods, which are also incorporated in PROC VARMAX. Volatility modeling has now become a standard part of time series modeling, because of the popularity of GARCH models. Both univariate and multivariate GARCH models are supported by PROC VARMAX. This feature is especially interesting for financial analytics in which risk is a focus. This book teaches with examples. Readers who are analyzing a time series for the first time will find PROC VARMAX easy to use; readers who know more advanced theoretical time series models will discover that PROC VARMAX is a useful tool for advanced model building.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Aimed at econometricians who have completed at least one course in time series modeling, Multiple Time Series Modeling Using the SAS VARMAX Procedure will teach you the time series analytical possibilities that SAS offers today. Estimations of model parameters are now performed in a split second. For this reason, working through the identifications phase to find the correct model is unnecessary. Instead, several competing models can be estimated, and their fit can be compared instantaneously. Consequently, for time series analysis, most of the Box and Jenkins analysis process for univariate series is now obsolete. The former days of looking at cross-correlations and pre-whitening are over, because distributed lag models are easily fitted by an automatic lag identification method. The same goes for bivariate and even multivariate models, for which PROC VARMAX models are automatically fitted. For these models, other interesting variations arise: Subjects like Granger causality testing, feedback, equilibrium, cointegration, and error correction are easily addressed by PROC VARMAX. One problem with multivariate modeling is that it includes many parameters, making parameterizations unstable. This instability can be compensated for by application of Bayesian methods, which are also incorporated in PROC VARMAX. Volatility modeling has now become a standard part of time series modeling, because of the popularity of GARCH models. Both univariate and multivariate GARCH models are supported by PROC VARMAX. This feature is especially interesting for financial analytics in which risk is a focus. This book teaches with examples. Readers who are analyzing a time series for the first time will find PROC VARMAX easy to use; readers who know more advanced theoretical time series models will discover that PROC VARMAX is a useful tool for advanced model building.

More books from SAS Institute

Cover of the book Fixed Effects Regression Methods for Longitudinal Data Using SAS by Anders Milhoj
Cover of the book JMP 14 Scripting Guide by Anders Milhoj
Cover of the book A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling, Second Edition by Anders Milhoj
Cover of the book Implementing CDISC Using SAS by Anders Milhoj
Cover of the book Applied Data Mining for Forecasting Using SAS by Anders Milhoj
Cover of the book SAS Business Intelligence for the Health Care Industry by Anders Milhoj
Cover of the book Decision Trees for Analytics Using SAS Enterprise Miner by Anders Milhoj
Cover of the book SAS Programming with Medicare Administrative Data by Anders Milhoj
Cover of the book JSL Companion by Anders Milhoj
Cover of the book Carpenter's Complete Guide to the SAS Macro Language, Third Edition by Anders Milhoj
Cover of the book SAS Certified Specialist Prep Guide by Anders Milhoj
Cover of the book How to Become a Top SAS Programmer by Anders Milhoj
Cover of the book JMP 14 JSL Syntax Reference by Anders Milhoj
Cover of the book JMP 14 Fitting Linear Models by Anders Milhoj
Cover of the book SAS Text Analytics for Business Applications by Anders Milhoj
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy