A new volatility model: GQARCH-ItO model

Volatility asymmetry is a hot topic in high-frequency financial market. This article proposes a new econometric model, which could describe volatility asymmetry based on high-frequency data and low-frequency data. After providing the quasi-maximum likelihood estimators for the parameters, we establish their asymptotic properties. We also conduct a series of simulation studies to check the finite sample performance and volatility forecasting performance of the proposed model and method. And a real data example is demonstrated that the new model has more substantial volatility prediction power than GARCH-Ito model in the literature.

Automated summary

This study introduces a new econometric model for volatility asymmetry and establishes its asymptotic properties. Through simulation studies, it is verified that the proposed model has better volatility forecasting performance than the GARCH-Ito model in the literature. A real data example further demonstrates the superior volatility prediction power of the new model.