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Limit Theory of Model Order Change-Point Estimator for GARCH Models

Irungu, Irene W., Mwita, Peter N., Waititu, Antony G. (2018) Limit Theory of Model Order Change-Point Estimator for GARCH Models. Journal of Mathematical Finance, 8 (2). pp. 426-445. ISSN 2162-2434. (doi:10.4236/jmf.2018.82027) (KAR id:97233)

Abstract

The limit theory of a change-point process which is based on the Manhattan distance of the sample autocorrelation function with applications to GARCH processes is examined. The general theory of the sample autocovariance and sample autocorrelation functions of a stationary GARCH process forms the basis of this study. Specifically the point processes theory is utilized to obtain their weak convergence limit at different lags. This is further extended to the change-point process. The limits are found to be generally random as a result of the infinite variance.

Item Type: Article
DOI/Identification number: 10.4236/jmf.2018.82027
Uncontrolled keywords: Autocorrelation Function, Change-Point, Convergence, GARCH, Manhattan Distance, Model Order, Point Process, Regular Variation, Weak Limit
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: Irene Irungu
Date Deposited: 30 Sep 2022 13:46 UTC
Last Modified: 03 Oct 2022 10:32 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/97233 (The current URI for this page, for reference purposes)

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