analyze empirical results for a selection of existing realized measures of volatility and incorporate them in a Realized GARCH … framework for the joint modeling of returns and realized measures of volatility. An influential bias in these measures is … over time, which stresses the importance of careful modeling and forecasting of volatility. We show that improved model fit …

framework can be used to estimate the autocorrelation function of the latent volatility process and a key persistence parameter …. Our analysis is motivated by the recent literature on realized (volatility) measures, such as the realized variance, that … are imperfect estimates of actual volatility. In an empirical analysis using realized measures for the DJIA stocks we find …

A stylized fact is that realized variance has long memory. We show that, when the instantaneous volatility is driven by …

based on low-frequency tick data tend to spuriously attribute a burst of volatility to the jump component thereby severely …

the key ingredient enabling inference about volatility and the presence of jumps in financial time series and is thus of …

variation and draw jump-robust inference about the diffusive volatility component, when a high-frequency record of asset prices …

We introduce the Realized Exponential GARCH model that can utilize multiple realized volatility measures for the … characterized by a flexible modeling of the dependence between returns and volatility. We apply the model to DJIA stocks and an …

realized volatility series with a time-varying parameters HAR model with exogenous variables. …