Volatility measurement with pockets of extreme return persistence

Abstract Increasing evidence points towards the episodic emergence of pockets with extreme return persistence. This notion refers to intraday periods non-trivial duration, for which stock returns are highly positively autocorrelated. Such episodes include, but not limited to, gradual jumps and prolonged bursts in drift component. In this paper, we develop a family integrated volatility estimators, labeled differenced-return ( DV ) provide robustness these types Ito semimartingale violations. Specifically, show that, by using differences consecutive high-frequency returns, our estimators can reduce bias that all commonly-used exhibit during such apparent short-term predictability. A Monte Carlo study demonstrates reliability newly developed finite samples. empirical forecasting application S&P 500 index futures individual equities, -based Heterogeneous Autoregressive (HAR) model performs well relative existing procedures according standard out-of-sample MSE QLIKE criteria.