A factor approach to realized volatility forecasting in the presence of finite jumps and cross-sectional correlation in pricing errors

There is a growing literature on the realized volatility (RV) forecasting of asset returns using high-frequency data. We explore the possibility of forecasting RV with factor analysis; once considering the significant jumps. A real high-frequency financial data application suggests that the factor based approach is of significant potential interest and novelty.