Projected Dynamic Conditional Correlations

Jordi Llorens-Terrazas and Christian Brownlees

International Journal of Forecasting, 2023, vol. 39, issue 4, 1761-1776

Abstract: We propose a novel specification of the Dynamic Conditional Correlation (DCC) model based on an alternative normalization of the pseudo-correlation matrix called Projected DCC (Pro-DCC). Our modification consists in projecting, rather than rescaling, the pseudo-correlation matrix onto the set of correlation matrices in order to obtain a well defined conditional correlation matrix. A simulation study shows that projecting performs better than rescaling when the dimensionality of the correlation matrix is large. An empirical application to the constituents of the S&P 100 shows that the proposed methodology performs favorably to the standard DCC in an out-of-sample asset allocation exercise.

Keywords: Multivariate volatility; DCC; Bregman projection; Nearest-correlation matrix; Stein’s loss (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:39:y:2023:i:4:p:1761-1776

DOI: 10.1016/j.ijforecast.2022.06.003

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