High frequency volatility forecasting considering jump and persistent leverage

Abstract

The similar characteristics and influence over long horizons with jump catch our attention to leverage. It is shown that a reduced-form model in discrete time can be significantly improved by considering a persistent leverage effect with a long-range dependence similar to that of volatility itself. To discovery more precise dynamic fluctuations, in the present work we first establish a positive and negative leverage HAR-RV model (PNL-HAR-RV-CJ), which is able to capture different impacts of positive and negative jumps on volatility at all the considered horizons. In the empirical research for the Shanghai composite index 5 minutes in Chinese stock market, we find that the newly established model shows better statistical and forecast features than conventional HAR-RV models.

Keywords:

• Jump
• Positive
• Negative
• Leverage
• Long memory
• Volatility
• HAR-RV model

AMS:

• 03C30