GENERALIZED AUTOREGRESSIVE CONDITIONAL CORRELATION

Michael McAleer, Felix Chan (), Suhejla Hoti and Offer Lieberman

Econometric Theory, 2008, vol. 24, issue 06, pages 1554-1583

Abstract: This paper develops a generalized autoregressive conditional correlation (GARCC) model when the standardized residuals follow a random coefficient vector autoregressive process. As a multivariate generalization of the Tsay (1987, Journal of the American Statistical Association 82, 590 350) dynamic conditional correlation (DCC) and the Tse and Tsui (2002, Journal of Business Economic Statistics 20, 351 150) is demonstrated to be a special case of a multivariate RCA process. A likelihood ratio test is proposed for several special cases of GARCC. The empirical usefulness of GARCC and the practicality of the likelihood ratio test are demonstrated for the daily returns of the Standard and Poor's 500, Nikkei, and Hang Seng indexes.

Date: 2008
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