Dynamic Equicorrelation

40 Pages Posted: 9 Mar 2009 Last revised: 10 Nov 2015

Robert F. Engle

New York University - Leonard N. Stern School of Business - Department of Economics; New York University (NYU) - Department of Finance; National Bureau of Economic Research (NBER)

Bryan T. Kelly

University of Chicago - Booth School of Business; National Bureau of Economic Research (NBER)

Date Written: June 1, 2011

Abstract

A new covariance matrix estimator is proposed under the assumption that at every time period all pairwise correlations are equal. This assumption, which is pragmatically applied in various areas of finance, makes it possible to estimate arbitrarily large covariance matrices with ease. The model, called DECO, involves first adjusting for individual volatilities and then estimating correlations. A quasi-maximum likelihood result shows that DECO provides consistent parameter estimates even when the equicorrelation assumption is violated. We demonstrate how to generalize DECO to block equicorrelation structures. DECO estimates for US stock return data show that (block) equicorrelated models can provide a better fit of the data than DCC. Using out-of-sample forecasts, DECO and Block DECO are shown to improve portfolio selection compared to an unrestricted dynamic correlation structure.

Suggested Citation

Engle, Robert F. and Kelly, Bryan T., Dynamic Equicorrelation (June 1, 2011). NYU Working Paper No. FIN-08-038; Chicago Booth Research Paper No. 12-07; Fama-Miller Working Paper. Available at SSRN: https://ssrn.com/abstract=1354525 or http://dx.doi.org/10.2139/ssrn.1354525

Robert F. Engle (Contact Author)

New York University - Leonard N. Stern School of Business - Department of Economics ( email )

269 Mercer Street
New York, NY 10003
United States

New York University (NYU) - Department of Finance

Stern School of Business
44 West 4th Street
New York, NY 10012-1126
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Bryan T. Kelly

University of Chicago - Booth School of Business ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States
773-702-8359 (Phone)

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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