correlations, and Section 7 discusses volatility forecast evaluation methods in both univariate and multivariate cases. Section 8 …

Realized covariance models specify the conditional expectation of a realized covariance matrix as a function of past … realized covariance matrices through a GARCH-type structure. We compare the forecasting performance of several such models in … impose the same dynamics to the variance and covariance processes (namely, BEKK-type models), whereas for the dataset of …

The intraday nonparametric estimation of the variance–covariance matrix adds to the literature in portfolio analysis of … the Greek equity market. This paper examines the economic value of various realized volatility and covariance estimators … under the strategy of volatility timing. I use three types of portfolios: Global Minimum Variance, Capital Market Line and …

This paper proposes a latent dynamic factor model for low- as well as high-dimensional realized covariance matrices of … positive definiteness of covariance matrices without imposing parametric restrictions. Simulated Bayesian parameter estimates … as well as positive definite (co)variance forecasts are obtained using Markov Chain Monte Carlo (MCMC) methods. An …