Growth rates of sample covariances of stationary symmetric [alpha]-stable processes associated with null recurrent Markov chains

Sidney Resnick, Gennady Samorodnitsky and Fang Xue

Stochastic Processes and their Applications, 2000, vol. 85, issue 2, 321-339

Abstract: A null recurrent Markov chain is associated with a stationary mixing S[alpha]S process. The resulting process exhibits such strong dependence that its sample covariance grows at a surprising rate which is slower than one would expect based on the fatness of the marginal distribution tails. An additional feature of the process is that the sample autocorrelations converge to non-random limits.

Keywords: Heavy; tails; Sample; covariance; ACF; Stable; process; Null; recurrent; Markov; chain (search for similar items in EconPapers)
Date: 2000
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304-4149(99)00081-2
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:spapps:v:85:y:2000:i:2:p:321-339

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

Access Statistics for this article

Stochastic Processes and their Applications is currently edited by T. Mikosch

More articles in Stochastic Processes and their Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().