Large dynamic covariance matrices: Enhancements based on intraday data

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