We develop a new parametric estimation procedure for option panels observed with error which relies on asymptotic … the spot volatility extracted from the options and the one obtained nonparametrically from high-frequency data on the … underlying asset. We further construct new formal tests of the model fit for specific regions of the volatility surface and for …

returns and the equity variance premium. The latter is increasing in risk aversion in a wide variety of economic settings. We … tackle several measurement issues assessing a plethora of state-of-the-art volatility forecasting models. We then examine the …

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 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 …

estimation of our model suggests that a newly discovered factor needs to clear a much higher hurdle, with a t-ratio greater than …

theory is quantitatively congruent with modest departures from random walk behavior with imprecise estimation of a well …

The equity premium, namely the expected return on the aggregate stock market less the government bill rate, is of …

multiple stochastic volatility processes. The estimation is based on annual consumption data from 1929 to 1959, monthly … are omitted from the estimation). Three independent volatility processes capture different frequency dynamics; our … predictable component and use high-frequency data, whenever available, to efficiently identify the volatility processes. Our …