Characterizing Interdependencies of Multiple Time Series
Theory and Applications
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Beschreibung
Presents an approach to characterizing the interdependencies of multivariate time series by means of the basic concept of the one-way effect
Shows how the third-series effect is eliminated with least causal distortion, introducing partial measures of the one-way effect, reciprocity, and association
Illustrates the proposed causal characterization by means of empirical applications to real data sets of the US macroeconomy and Japan’s financial economy
Presents an approach to characterizing the interdependencies of multivariate time series by means of the basic concept of the one-way effect Shows how the third-series effect is eliminated with least causal distortion, introducing partial measures of the one-way effect, reciprocity, and association Illustrates the proposed causal characterization by means of empirical applications to real data sets of the US macroeconomy and Japan’s financial economy Includes supplementary material: sn.pub/extras
Autor*in
Yuzo Hosoya
Themen in »Characterizing Interdependencies of Multiple Time Series«
Autoregressive Moving-average Model Canonical Factorization Causal Analysis Large Sample Test Prediction Error
Stimmen zu »Characterizing Interdependencies of Multiple Time Series«
“This book is concerned with concepts and methods for characterizing interdependencies of multiple time series in the frequency domain. … the authors have written an interesting and high valuable book, with emphasis on the practical analysis of time series. At the end of each chapter, a short list of references is provided and this will help a reader wishing to pursue this area further.” (Apostolos Batsidis, zbMATH 1387.62003, 2018)
“This is very nicely written book on interdependence measures between time series. The exposition is clear and the book is enriched with various examples and applications. Basic knowledge of time-series analysis is assumed. The book should trun out to be very useful for statisticians, econometricians or time-series analysts.” (Alexander M. Lindner, Mathematical Reviews, February, 2019)
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