Chapter

Univariate periodic time series models

Philip Hans Franses and Richard Paap

in Periodic Time Series Models

Published in print March 2004 | ISBN: 9780199242023
Published online August 2004 | e-ISBN: 9780191601286 | DOI: http://dx.doi.org/10.1093/019924202X.003.0003

Series: Advanced Texts in Econometrics

 Univariate periodic time series models

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In Chapter 3 we outline the basics of periodic models for univariate time series data. We abstain from a discussion of trending data, and assume there are no stochastic trends. We consider two types of representation of periodic models. We discuss how parameters can be estimated, how the lag structures can be determined, and we give diagnostic measures to examine if the models are properly specified. Next, we show how one can generate forecasts from periodic models. As it is of interest to see what happens when one neglects periodicity, we also dedicate a section to this topic. Finally, we discuss periodic models for the conditional second moment, that is, periodic GARCH models.

Keywords: Periodic autoregression; parameter estimation; model specification; periodic GARCH

Chapter.  16176 words. 

Subjects: Econometrics and Mathematical Economics

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