ON THE SQUARED RESIDUAL AUTOCORRELATIONS IN NON‐LINEAR TIME SERIES WITH CONDITIONAL HETEROSKEDASTICITY

W. K. Li and T. K. Mak

Journal of Time Series Analysis, 1994, vol. 15, issue 6, 627-636

Abstract: Abstract. Time series with a changing conditional variance have been found useful in many applications. Residual autocorrelations from traditional autoregressive moving‐average models have been found useful in model diagnostic checking. By analogy, squared residual autocorrelations from fitted conditional heteroskedastic time series models would be useful in checking the adequacy of such models. In this paper, a general class of squared residual autocorrelations is defined and their asymptotic distribution is obtained. The result leads to some useful diagnostic tools for statisticians using conditional heteroskedastic time series models. Some simulation results and an illustrative example are also reported.

Date: 1994
References: Add references at CitEc
Citations: View citations in EconPapers (103)

Downloads: (external link)
https://doi.org/10.1111/j.1467-9892.1994.tb00217.x

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:bla:jtsera:v:15:y:1994:i:6:p:627-636

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0143-9782

Access Statistics for this article

Journal of Time Series Analysis is currently edited by M.B. Priestley

More articles in Journal of Time Series Analysis from Wiley Blackwell
Bibliographic data for series maintained by Wiley Content Delivery ().