Bolstering the Modelling and Forecasting of Realized Covariance Matrices using (Directional) Common Jumps

This paper proposes a robust framework for disentangling undiversifiable common jumps within the realized covariance matrix. Simultaneous jumps detected in our empirical study are strongly related to major financial and economic news, and their occurrence raises correlation and persistence among assets. Our application to 20 Dow Jones stocks, shows that common jumps and directional common jumps substantially improve the in- and out-of-sample forecasts of the realized covariances at the day-, week- and month-horizon. Applying these new specifications to minimum variance portfolios results in superior positions from reduced turnover. The implication is that investors willingly sacrifice up to 100 annual basis points in switching to those strategies