Large Dynamic Covariance Matrices: Enhancements Based on Intraday Data

University of Zurich, Department of Economics, Working Paper No. 356, July 2020

36 Pages Posted: 25 Sep 2020

See all articles by Gianluca De Nard

Gianluca De Nard

University of Zurich - Department of Banking and Finance

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: July 1, 2020

Abstract

Modeling and forecasting dynamic (or time-varying) covariance matrices has many important applications in finance, such as Markowitz portfolio selection. A popular tool to this end are multivariate GARCH models. Historically, such models did 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 covariances, is the concept of a regularized return, obtained from a volatility proxy in conjunction with a smoothed sign (function) 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 (July 1, 2020). University of Zurich, Department of Economics, Working Paper No. 356, July 2020, 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

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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