25 janvier 2019
Realized SemiCovariances: Looking for Signs of Direction Inside the Covariance Matrix
Tim Bollerslev, Duke University
We propose a new decomposition of the realized covariance matrix into four “realized semicovariance” components based on the signs of the underlying high-frequency returns. We derive the asymptotic distribution for the different components under the assumption of a continuous multivariate semimartingale and standard in fill asymptotic arguments. Based on high-frequency returns for a large cross-section of individual stocks, we document distinctly different features and dynamic dependencies in the different semicovariance components. We demonstrate that the accuracy of portfolio return variance forecasts may be significantly improved by exploiting these differences and “looking inside” the realized covariance matrices for signs of direction.
(co-authored by Andrew J. Patton (Duke University) and Rogier Quaedvlieg (Erasmus University Rotterdam)
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