skip to content

Faculty of Economics

Journal Cover

Harvey, A. C.and Thiele, S.

Testing against changing correlation

Journal of Empirical Finance

Vol. 38(B) pp. 575-589 (2016)

Abstract: A test for time-varying correlation is developed within the framework of a dynamic conditional score (DCS) model for both Gaussian and Student t-distributions. The test may be interpreted as a Lagrange multiplier test and modified to allow for the estimation of models for time-varying volatility in the individual series. Unlike standard moment-based tests, the score-based test statistic includes information on the level of correlation under the null hypothesis and local power arguments indicate the benefits of doing so. A simulation study shows that the performance of the score-based test is strong relative to existing tests across a range of data generating processes. An application to the Hong Kong and South Korean equity markets shows that the new test reveals changes in correlation that are not detected by the standard moment-based test.

Keywords: Dynamic conditional score, EGARCH, Lagrange multiplier test, Portmanteau test, time-varying covariance matrices

JEL Codes: C12, C32, G15

Author links: Andrew Harvey  

Publisher's Link: https://doi.org/10.1016/j.jempfin.2015.09.003



Cambridge Working Paper in Economics Version of Paper: Testing against Changing Correlation, Harvey, A. C. and Thiele, S., (2014)

Papers and Publications



Recent Publications


Elliott, M., Golub, B. and Leduc, M. V. Supply Network Formation and Fragility American Economic Review [2022]

Bhattacharya, D., Dupas, P. and Kanaya, S. Demand and Welfare Analysis in Discrete Choice Models with Social Interactions Review of Economic Studies [2023]

Chen, J., Elliott, M. and Koh, A. Capability Accumulation and Conglomeratization in the Information Age Journal of Economic Theory [2023]

Bhattacharya, D. and Komarova, T. Incorporating Social Welfare in Program-Evaluation and Treatment Choice Review of Economics and Statistics, accepted [2023]