A test for constant correlations in a multivariate GARCH model

We introduce a Lagrange Multiplier (LM) test for the constant-correlation h ypothesis in a multivariate GARCH model. The test examines the restrictions imposed on a model which encompasses the constant-correlation multivariate GARCH model. It requires the estimates of the constant-correlation model o nly and is computationally convenient. We report some Monte Carlo results o n the finite-sample properties of the LM statistic. The LM test is compared against the Information Matrix (IM) test due to Bera and Kim (1996). The L M test appears to have good power against the alternatives considered and i s more robust to nonnormality. We apply the test to three data sets, namely , spot-futures prices, foreign exchange rates and stock market returns. The results show that the spot-futures and foreign exchange data have constant correlations, while the correlations across national stock market returns are time varying. (C) 2000 Elsevier Science S.A. All rights reserved.