This paper comprehensively investigates the role of realized jumps detected from high frequency data in predicting future volatility from both statistical and economic perspectives. Using seven major jump tests, we show that separating jumps from diffusion improves volatility forecasting both...

We propose a least squares regression framework for the estimation of the realized covariation matrix using high frequency data. The new estimator is robust to market microstructure noise (MMS) and non-synchronous trading. Comprehensive simulation and empirical analysis show that our estimator...

This paper develops the idea of renewal time sampling, a novel sampling scheme constructed from stopping times of semimartingales. Based on this new sampling scheme we propose a class of volatility estimators named renewal based volatility estimators. In this paper we show that: (1) The spot...