Negative Positive
Title: Multivariate Tests for Time Series Models
Review: This text is a collection of tests for multivariate time series models. While by no means comprehensive, this is a concise and well written text that extends to the multivariate case the necessary tests that are performed for the more commonly generated univariate time series models. I was pleasantly surprised at the job that the authors performed in developing some of the important ideas, as opposed to simply presenting equations.In the text, methods covered include testing for joint stationarity, normality, independence, cointegration, and causality. There is also a section on the specification of multivariate linear models. Unfortunately, discussion of multivariate nonlinear models amounts primarily to literature references. Finally, there is a discussion of testing for model order and forecast accuracy. Overall, I found this to be a highly useful text.
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