This paper proposes two new approaches to improve estimation of the coefficients of the multivariate HAR (MHAR) model, and in turn improve forecast performance. A robust estimator of the covariance matrix is adopted to replace the realized covariance (RCov) matrix while estimating the MHAR...

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 is the first comprehensive study on the forecasting of the realized volatility of non-ferrous metal futures. Based on 8.5 years of intraday data on copper, zinc, nickel, lead and aluminum, we explore a variety of extensions of the univariate heterogeneous autoregressive (HAR) model and seek...