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Periodic Time Series Models$
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Philip Hans Franses and Richard Paap

Print publication date: 2004

Print ISBN-13: 9780199242023

Published to Oxford Scholarship Online: August 2004

DOI: 10.1093/019924202X.001.0001

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Univariate periodic time series models

Univariate periodic time series models

Chapter:
(p.27) 3 Univariate periodic time series models
Source:
Periodic Time Series Models
Author(s):

Philip Hans Franses (Contributor Webpage)

Richard Paap (Contributor Webpage)

Publisher:
Oxford University Press
DOI:10.1093/019924202X.003.0003

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

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