This paper introduces a multivariate kernel based forecasting tool for the prediction of variance-covariance matrices of stock returns. The method introduced allows for the incorporation of macroeconomic variables into the forecasting process of the matrix without resorting to a decomposition of...

This paper proposes a novel decomposition of realized volatility (RV) into moderate and extreme realized volatility estimates. These estimates behave like long and short term components of volatility, and are very different from either realized semi-variance or the continuous and jump components...