or a particular conditionally heteroscedastic nonlinear (ARCH)
process for which the conditional variance of the observable sequence $r_t$ is
the square of an inhomogeneous linear combination of $r_s, s < t$, we give
conditions under which, for integers $l \geq 2, r_t^l$ has long memory
autocorrelation and normalized partial sums of $r_t^l$ converge to fractional
Brownian motion.
Publié le : 2000-08-14
Classification:
ARCH processes,
long memory,
Volterra series,
diagrams,
central limit theorem,
fractioinal Brownian motion,
62M10,
60G18
@article{1019487516,
author = {Giraitis, Liudas and Robinson, Peter M. and Surgailis, Donatas},
title = {A model for long memory conditional heteroscedasticity},
journal = {Ann. Appl. Probab.},
volume = {10},
number = {2},
year = {2000},
pages = { 1002-1024},
language = {en},
url = {http://dml.mathdoc.fr/item/1019487516}
}
Giraitis, Liudas; Robinson, Peter M.; Surgailis, Donatas. A model for long memory conditional heteroscedasticity. Ann. Appl. Probab., Tome 10 (2000) no. 2, pp. 1002-1024. http://gdmltest.u-ga.fr/item/1019487516/