parameters of the best linear approximation is characterized via its support function, and limit theory is developed for the …

that background, we explore whether incorporating stochastic volatility improves DSGE forecasts (point, interval, and … policy rate. We find that incorporating stochastic volatility in DSGE models of macroeconomic fundamentals markedly improves … their density forecasts, just as incorporating stochastic volatility in models of financial asset returns improves their …

-diffusions, and models of stochastic volatility. This paper explores the statistical properties of these models with a view to …

Volatility has been one of the most active areas of research in empirical finance and time series econometrics during … categorizing the various volatility concepts, measurement procedures, and modeling procedures. We define three different volatility … concepts: (i) the notional volatility corresponding to the ex-post sample-path return variability over a fixed time interval …

Recently there has been a great deal of interest in modeling volatility fluctuations. ARCH models, for example, provide … parsimonious approximations to volatility dynamics. Here we provide a selective amount of certain aspects of conditional volatility …

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

It appears that volatility in equity markets is asymmetric: returns and conditional volatility are negatively … correlated. We provide a unified framework to simultaneously investigate asymmetric volatility at the firm and the market level … empirical evidence on asymmetry to Japanese stocks. Although volatility asymmetry is present and significant at the market and …