文章基本信息

标题：Limit Theory of Model Order Change-Point Estimator for GARCH Models
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作者：Irene W. Irungu ; Peter N. Mwita ; Antony G. Waititu 等
期刊名称：Journal of Mathematical Finance
印刷版ISSN：2162-2434
电子版ISSN：2162-2442
出版年度：2018
卷号：08
期号：02
页码：426-445
DOI：10.4236/jmf.2018.82027
语种：English
出版社：Scientific Research Publishing
摘要：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.
关键词：Autocorrelation Function;Change-Point;Convergence;GARCH;Manhattan Distance;Model Order;Point Process;Regular Variation;Weak Limit