Volatility permeates modern financial theories and decision making processes. As such, accurate measures and good … forecasts of future volatility are critical for the implementation and evaluation of asset pricing theories. In response to this …, a voluminous literature has emerged for modeling the temporal dependencies in financial market volatility at the daily …

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 … variation, we formally develop the links between the conditional covariancematrix and the concept of realized volatility. Next …

" states - following market declines and when market volatility is high - and are contemporaneous with market rebounds. We show …

Most affine models of the term structure with stochastic volatility (SV) predict that the variance of the short rate is … stochastic volatility (USV)." Of the models tested, only the A1(4) USV model is found to generate both realistic volatility … estimates and a good cross-sectional fit. Our findings suggests that interest rate volatility cannot be extracted from the cross …

alleviate microstructure frictions for realized volatility estimation. Size and power of the procedure are explored through … intraday data and nonparametric volatility measures, along with a new jump detection technique and appropriate conditional …

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 … inherently latent, and Section 1 begins with a brief intuitive account of various key volatility concepts. Section 2 then …