We nest multiple volatility components, fat tails and a U-shaped pricing kernel in a single option model and compare their contribution to describing returns and option data. All three features lead to statistically significant model improvements. A U-shaped pricing kernel is economically most...

We survey the theory and empirical evidence on GARCH option valuation models. We provide an overview of different functional forms for the volatility dynamic, multifactor models, nonnormal innovation distributions and valuation techniques. We also discuss alternative pricing kernels used for...

This chapter surveys the methods available for extracting information from option prices that can be used in forecasting. We consider option-implied volatilities, skewness, kurtosis, and densities. More generally, we discuss how any forecasting object that is a twice differentiable function of...

Many studies have documented that daily realized volatility estimates based on intraday returns provide volatility forecasts that are superior to forecasts constructed from daily returns only. We investigate whether these forecasting improvements translate into economic value added. To do so we...

We survey the recent academic literature that uses option-implied information to construct equity portfolios. Studies show that equity managers can earn a positive alpha by using information in individual equity options, by using stocks' exposure to information in market index options, and by...

We present a new discrete-time GARCH jump framework that allows for rich dynamics in higher moments by combining heteroskedastic processes with fat-tailed innovations in returns and volatility. We provide a tractable risk neutralization framework allowing for option valuation with separate...