Work

Large dynamic covariance matrices: Enhancements based on intraday data

Year: 2022

Type: article

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.

Source: Journal of Banking & Finance

DOI: 10.1016/j.jbankfin.2022.106426

Authors: Gianluca De Nard, Robert F. Engle, Olivier Ledoit, Michael Wolf

Institutions: University of Zurich, New York University

Language: English

Topic: Financial Risk and Volatility Modeling

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $2,620

OpenAlex ID: W4225865461

FWCI: 5.677

Cites: 37

Cited by: 39

Related to: 10