volatility forecast, coupled with a parametric lognormal-normal mixture distribution implied by the theoretically and empirically … forecasting of daily and lower frequency volatility and return distributions. Most procedures for modeling and forecasting … ARCH or stochastic volatility models, which often perform poorly at intraday frequencies. Use of realized volatility …

volatility forecast, coupled with a parametric lognormal-normal mixture distribution implied by the theoretically and empirically … forecasting of daily and lower frequency volatility and return distributions. Most procedures for modeling and forecasting … ARCH or stochastic volatility models, which often perform poorly at intraday frequencies. Use of realized volatility …

correlations, and Section 7 discusses volatility forecast evaluation methods in both univariate and multivariate cases. Section 8 …Volatility has been one of the most active and successful areas of research in time series econometrics and economic … empirical insights to emerge from this burgeoning literature, with a distinct focus on forecasting applications. Volatility is …

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 …