In this study, we investigate whether low-frequency data improve volatility forecasting when
high-frequency data are available. To answer this question, we utilize four forecast …

We propose a bootstrap method for estimating the distribution (and functionals of it such as
the variance) of various integrated covariance matrix estimators. In particular, we first adapt …

The main contribution of this paper is to propose a bootstrap method for inference on
integrated volatility based on the pre-averaging approach, where the pre-averaging is done …

In this paper, we study the Edgeworth expansion for a pre-averaging estimator of quadratic
variation in the framework of continuous diffusion models observed with noise. More …

We derive local (over a small time interval∆) Edgeworth expansions of the bivariate
conditional characteristic function of the level/volatility∆-increments of a Brownian semi …

This article introduces a local Gaussian bootstrap method useful for the estimation of the
asymptotic distribution of high-frequency data-based statistics such as functions of realized …

We develop Edgeworth expansion theory for spot volatility estimator under general
assumptions on the log-price process that allow for drift and leverage effect. The result is …

We put forward a new method to construct jump‐robust estimators of integrated volatility,
namely realized information variation (RIV) and realized information power variation (RIPV) …

This paper introduces empirical likelihood methods for interval estimation and hypothesis
testing on volatility measures in some high frequency data environments. We propose a …

Volatility functionals are widely used in financial econometrics. In the literature, they are
estimated with realized volatility functionals using high-frequency data. In this paper we …