Weak convergence of multivariate partial maxima processes

Danijel Krizmanić

Journal of Multivariate Analysis, 2017, vol. 155, issue C, 1-11

Abstract: For a strictly stationary sequence of R+d–valued random vectors we derive functional convergence of partial maxima stochastic processes under joint regular variation and weak dependence conditions. The limit process is an extremal process and the convergence takes place in the space of R+d–valued càdlàg functions on [0,1], with the Skorohod weak M1 topology. We also show that this topology in general cannot be replaced by the stronger (standard) M1 topology. The theory is illustrated on three examples, including the multivariate squared GARCH process with constant conditional correlations.

Keywords: Functional limit theorem; Regular variation; Weak M1 topology; Extremal process; Weak convergence; Multivariate GARCH (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0047259X16301889
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:155:y:2017:i:c:p:1-11

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.jmva.2016.11.012

Access Statistics for this article

Journal of Multivariate Analysis is currently edited by de Leeuw, J.

More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().