using volatility impulse response analysis. The data set features ten years of daily returns series for the New York Stock … independent shocks on volatility through time, while avoiding typical orthogonalization and ordering problems. Volatility impulse … response functions (VIRF) provide information about the impact of independent shocks on volatility. HHś VIRF extends a …

contribution to overall realized variation and their contribution to predictive regressions of realized volatility. We find … individual stocks. -- Itô semi-martingale ; realized volatility ; jumps ; quadratic volatility ; multipower variation ; tripower …

Heteroscedasticity) volatility dynamics. DCS models are robust to extreme observations, whereas standard financial time series models are … observations, stochastic seasonality with dynamic amplitude, and volatility dynamics. These seasonality dynamics of the GTQ/USD are …

Measuring and modeling financial volatility is the key to derivative pricing, asset allocation and risk management … the daily or lower frequency volatility can be obtained by summing over squared high-frequency returns.In turn, this so …-called realized volatility can be used for more accurate model evaluation and description of the dynamic and distributional structure …

particularly interested in volatility modelling and forecasting given their importance for FOREX dealers. Compared with previous … ; volatility …

. -- High frequency data ; long memory ; volatility persistence ; structural breaks …