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Realized Semicovariances
Author(s) -
Bollerslev Tim,
Li Jia,
Patton Andrew J.,
Quaedvlieg Rogier
Publication year - 2020
Publication title -
econometrica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 16.7
H-Index - 199
eISSN - 1468-0262
pISSN - 0012-9682
DOI - 10.3982/ecta17056
Subject(s) - sign (mathematics) , leverage (statistics) , portfolio , covariance , realized variance , covariance matrix , mathematics , variance (accounting) , econometrics , statistics , mathematical analysis , economics , volatility (finance) , accounting , financial economics
We propose a decomposition of the realized covariance matrix into components based on the signs of the underlying high‐frequency returns, and we derive the asymptotic properties of the resulting realized semicovariance measures as the sampling interval goes to zero. The first‐order asymptotic results highlight how the same‐sign and mixed‐sign components load differently on economic information related to stochastic correlation and jumps. The second‐order asymptotic results reveal the structure underlying the same‐sign semicovariances, as manifested in the form of co‐drifting and dynamic “leverage” effects. In line with this anatomy, we use data on a large cross‐section of individual stocks to empirically document distinct dynamic dependencies in the different realized semicovariance components. We show that the accuracy of portfolio return variance forecasts may be significantly improved by exploiting the information in realized semicovariances.