Detecting and diagnostic checking multivariate conditional heteroscedastic time series models

H. WONG, Wai Keung LI

Research output: Contribution to journalArticlespeer-review

10 Citations (Scopus)

Abstract

Two tests for multivariate conditional heteroscedastic models are proposed. One is based on the cross-correlations of standardized squared residuals and the other is a score (Lagrange multiplier) test. The cross-correlations test can be used to detect the presence of multivariate conditional heteroscedasticity whereas the other test can be used for diagnostic checking. Simulation studies on the size and power of the test statistics are reported. The application of the tests is illustrated by an example using the S & P 500 and Sydney All Ordinary Indexes. Copyright © 2002 The Institute of Statistical Mathematics.
Original languageEnglish
Pages (from-to)45-59
JournalAnnals of the Institute of Statistical Mathematics
Volume54
Issue number1
DOIs
Publication statusPublished - Mar 2002

Citation

Wong, H., & Li, W. K. (2002). Detecting and diagnostic checking multivariate conditional heteroscedastic time series models. Annals of the Institute of Statistical Mathematics, 54(1), 45-59. doi: 10.1023/A:1016161620735

Keywords

  • ARCH models
  • Squared residuals
  • Cross-correlation tests
  • Score test

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