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

dc.contributor.author	Irungu, Irene W.
dc.contributor.author	Mwita, Peter N.
dc.contributor.author	Waititu, Antony G.
dc.date.accessioned	2019-08-21T06:42:23Z
dc.date.available	2019-08-21T06:42:23Z
dc.date.issued	2018
dc.identifier.issn	2162-2442
dc.identifier.uri	http://ir.mksu.ac.ke/handle/123456780/4745
dc.description.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	en_US
dc.language.iso	en_US	en_US
dc.publisher	Scientific Research Publishing	en_US
dc.subject	Autocorrelation Function	en_US
dc.subject	Change-Point	en_US
dc.subject	Convergence	en_US
dc.subject	GARCH	en_US
dc.subject	Manhattan Distance	en_US
dc.subject	Model Order	en_US
dc.subject	Point Process	en_US
dc.subject	Regular Variation	en_US
dc.subject	Weak Limit	en_US
dc.title	Limit Theory of Model Order Change-Point Estimator for GARCH Mode	en_US
dc.type	Article	en_US

School of Pure and Applied Sciences [259]
Scholarly Articles by Faculty & Students in the School of Pure and Applied Sciences