ABSTRACT
Since the mid-1990s, the availability of high-frequency data attracted considerable interest in the econometric, statistical, and financial literature. On the one side, many authors considered the filtering problems associated with these data, their use for market microstructure studies, or their direct modeling (see Dacorogna et al. 2001 for a survey). On the other side, high-frequency data gave rise to a relevant research area, that of realized volatility, started by the seminal contributions of Andersen et al. (2000), Andersen et al. (2001a), and Andersen et al. (2001b). This strand of the financial econometrics literature could be further divided into two subsets, the first including the theoretical studies dealing with the appropriate measurement of the realized volatility, and the second, more empirical, tackling the problem of modeling realized volatility sequences for their financial applications (see the paper by McAleer and Medeiros 2008 for a survey).
