We argue for incorporating the financial economics of market microstructure into the financial econometrics of asset return volatility estimation. In particular, we use market microstructure theory to derive the cross-correlation function between latent returns and market microstructure noise,...

Recent evidence shows that U.S. price momentum strategies suffer tremendous losses in times of highly volatile market recoveries. We extend the existing literature by analyzing the performance of both price and earnings momentum portfolios across different market states. For our German sample,...

Short sellers have been routinely blamed for triggering, or exacerbating, stock market declines. The experience of Taiwan provides an interesting case study of the impact of short selling bans on stock returns volatility in a time series framework due to the length of time the short selling ban...

Short sellers have been routinely blamed for triggering, or exacerbating, stock market declines. The experience of Taiwan provides an interesting case study of the impact of short selling bans on stock returns volatility in a time series framework due to the length of time the short selling ban...

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...

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...

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...