A rapidly growing literature has documented important improvements in volatility measurement and forecasting … provides a practical framework for non-parametrically measuring the jump component in realized volatility measurements … an easy-to-implement reduced form model for realized volatility results in highly significant jump coefficient estimates …

The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this … paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility …, which accommodates level shifts, day-of-the-week effects, leverage effects and volatility level effects. Applying the model …

We introduce a statistical test for simultaneous jumps in the price of a financial asset and its volatility process … volatility jumps, we design and analyze a nonparametric spectral estimator of the spot volatility process. A simulation study and … important role played by price volatility co-jumps. …

of volatility in finance for portfolio allocation, derivative pricing and risk management. The method has a two … average realized volatility processes can achieve a convergence rate close to OP(n−4/9) , which is better than the convergence … based on average realized volatility processes indeed performs better than that based on the price processes. Empirically …

This paper examines the impact of intraday periodicity on forecasting realized volatility using a heterogeneous … autoregressive model (HAR) framework. We show that periodicity inflates the variance of the realized volatility and biases jump …