tackle several measurement issues assessing a plethora of state-of-the-art volatility forecasting models. We then examine the …

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 … and forecasting. Building on the theory of continuous-time arbitrage-free price processes and the theory of quadratic …

We exploit direct model-free measures of daily equity return volatility and correlation obtained from high …, solidify and extend existing characterizations of stock return volatility and correlation. We find that the unconditional … portfolio diversification when the market is most volatile. Our findings are broadly consistent with a latent volatility fact or …

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 …

-shifts of heterogeneous durations affect the volatility of dividend news. We estimate tightly parameterized specifications with … likelihood than the classic Campbell and Hentschel (1992) specification, while generating volatility feedback effects 6 to 12 … times larger. We show in an extension that Bayesian learning about stochastic volatility is faster for bad states than good …

In this paper we show that measures of economic uncertainty (conditional volatility of consumption) predict and are …

This paper presents and implements statistical tests of stock market forecastability and volatility that are immune …