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Large dynamic covariance matrices: enhancements based on intraday data


De Nard, Gianluca; Engle, Robert F; Ledoit, Olivier; Wolf, Michael (2022). Large dynamic covariance matrices: enhancements based on intraday data. Working paper series / Department of Economics 356, University of Zurich.

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.

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.

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Additional indexing

Item Type:Working Paper
Communities & Collections:03 Faculty of Economics > Department of Economics
Working Paper Series > Department of Economics
Dewey Decimal Classification:330 Economics
JEL Classification:C13, C58, G11
Uncontrolled Keywords:Dynamic conditional correlations, intraday data, Markowitz portfolio selection, multivariate GARCH, nonlinear shrinkage
Language:English
Date:January 2022
Deposited On:28 Jul 2020 06:41
Last Modified:20 Jun 2022 13:57
Series Name:Working paper series / Department of Economics
Number of Pages:40
ISSN:1664-705X
Additional Information:Revised version
OA Status:Green
Official URL:https://www.econ.uzh.ch/en/research/workingpapers.html?paper-id=1038
  • Content: Updated Version
  • Description: Revised version January 2022