On the squared residual autocorrelations in non-linear time series with conditional heteroskedasticity

Wai Keung LI, T. K. MAK

Research output: Contribution to journalArticles

142 Citations (Scopus)

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. Copyright © 1994 Wiley Blackwell. All rights reserved.
Original languageEnglish
Pages (from-to)627-636
JournalJournal of Time Series Analysis
Volume15
Issue number6
DOIs
Publication statusPublished - Nov 1994

Citation

Li, W. K., & Mak, T. K. (1994). On the squared residual autocorrelations in non-linear time series with conditional heteroskedasticity. Journal of Time Series Analysis, 15(6), 627-636. doi: 10.1111/j.1467-9892.1994.tb00217.x

Keywords

  • Asymptotic distribution
  • Conditional heteroskedasticity
  • Model diagnostic checking
  • Squared residual autocorrelations

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