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 …

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 …

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 …

estimation of stochastic volatility models. We show both theoretically and empirically that the log range is approximately …We propose using the price range, a recently-neglected volatility proxy with a long histoy in finance, in the … Gaussian, in sharp contrast to popular volatility proxies, such as log absolute or squared returns. Hence Gaussian quasi …