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Published in:
Data in the 21st Century Read chapter Read first chapter

2018 | OriginalPaper | Chapter

On Parameter Change Test for ARMA Models with Martingale Difference Errors

Authors : Haejune Oh, Sangyeol Lee

Published in: Predictive Econometrics and Big Data

Publisher: Springer International Publishing

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Abstract

This study considers the CUSUM test for ARMA models with stationary martingale difference errors. CUSUM tests are widely used for detecting abrupt changes in time series models. Although they perform adequately in general, their performance is occasionally unsatisfactory in ARMA models. This motivates us to design a new test that can simultaneously detect the ARMA parameter and variance changes. Its null limiting distribution is derived under regularity conditions. Monte Carlo simulations confirm the validity of the proposed test.

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previous chapter Joint Plausibility Regions for Parameters of Skew Normal Family
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Metadata
Title
On Parameter Change Test for ARMA Models with Martingale Difference Errors
Authors
Haejune Oh
Sangyeol Lee
Copyright Year
2018
Book
Predictive Econometrics and Big Data

Print ISBN: 978-3-319-70941-3

Electronic ISBN: 978-3-319-70942-0

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-70942-0_17

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