Large Dynamic Covariance Matrices: Enhancements Based on Intraday Data

University of Zurich, Department of Economics, Working Paper No. 356, Revised version

39 Pages Posted: 25 Sep 2020 Last revised: 30 Jun 2021

See all articles by Gianluca De Nard

Gianluca De Nard

University of Zurich - Department of Banking and Finance; New York University

Robert F. Engle

New York University (NYU) - Department of Finance; National Bureau of Economic Research (NBER); New York University (NYU) - Volatility and Risk Institute

Olivier Ledoit

University of Zurich - Department of Economics

Michael Wolf

University of Zurich - Department of Economics

Date Written: June 2021

Abstract

Multivariate GARCH models do not perform well in large dimensions due to the so-called curse of dimensionality. The recent DCC-NL model of Engle et al. (2019) is able to overcome this curse via nonlinear shrinkage estimation of the unconditional correlation matrix. In this paper, we show how performance can be increased further by using open/high/low/close (OHLC) price data instead of simply using daily returns. A key innovation, for the improved modeling of not only dynamic variances but also of dynamic correlations, is the concept of a regularized return, obtained from a volatility proxy in conjunction with a smoothed sign of the observed return.

Keywords: Dynamic conditional correlations, intraday data, Markowitz portfolio selection, multivariate GARCH, nonlinear shrinkage

JEL Classification: C13, C58, G11

Suggested Citation

De Nard, Gianluca and Engle, Robert F. and Ledoit, Olivier and Wolf, Michael, Large Dynamic Covariance Matrices: Enhancements Based on Intraday Data (June 2021). University of Zurich, Department of Economics, Working Paper No. 356, Revised version, Available at SSRN: https://ssrn.com/abstract=3662143 or http://dx.doi.org/10.2139/ssrn.3662143

Gianluca De Nard

University of Zurich - Department of Banking and Finance ( email )

Zürichbergstrasse 14
Zürich, Zürich CH-8032
Switzerland

HOME PAGE: http://denard.ch

New York University ( email )

Department of Finance
NYU Stern Volatility and Risk Institute
New York, NY
United States

HOME PAGE: http://https://vlab.stern.nyu.edu

Robert F. Engle (Contact Author)

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

New York University (NYU) - Volatility and Risk Institute ( email )

44 West 4th Street
New York, NY 10012
United States

Olivier Ledoit

University of Zurich - Department of Economics ( email )

Wilfriedstrasse 6
Zürich, 8032
Switzerland

Michael Wolf

University of Zurich - Department of Economics ( email )

Wilfriedstrasse 6
Zurich, 8032
Switzerland

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