This paper presents a new model for the valuation of European options, in which the volatility of returns consists of two components. One of these components is a long-run component, and it can be modeled as fully persistent. The other component is short-run and has a zero mean. Our model can be...

We survey the theory and empirical evidence on GARCH option valuation models. Our treatment includes the range of functional forms available for the volatility dynamic, multifactor models, nonnormal shock distributions as well as style of pricing kernels typically used. Various strategies for...

Recent work by Engle and Lee (1999) shows that allowing for long-run and short-run components greatly enhances a GARCH model’s ability fit daily equity return dynamics. Using the risk-neutralization in Duan (1995), we assess the option valuation performance of the Engle-Lee model and compare...

Most recent empirical option valuation studies build on the affine square root (SQR) stochastic volatility model. The SQR model is a convenient choice, because it yields closed-form solutions for option prices. However, relatively little is known about the resulting biases. We investigate...

Few issues are more important for finance practice than the computation of market betas. Existing approaches compute market betas using historical data. While these approaches differ in terms of statistical sophistication and the modeling of the time-variation in the betas, they are all...

We provide results for the valuation of European style contingent claims for a large class of specifications of the underlying asset returns. Our valuation results obtain in a discrete time, infinite state-space setup using the no-arbitrage principle and an equivalent martingale measure. Our...

State-of-the-art stochastic volatility models generate a "volatility smirk" that explains why out-of-the-money index puts have high prices relative to the Black-Scholes benchmark. These models also adequately explain how the volatility smirk moves up and down in response to changes in risk....

Yes. We use intraday data to compute weekly realized variance, skewness and kurtosis for individual equities and assess whether this week?s realized moments predict next week?s stock returns in the cross-section. We sort stocks each week according to their past realized moments, form decile...

Illiquidity is well-known to be a signi?cant determinant of stock and bond returns. We report on illiquidity premia in equity option markets. An increase in option illiquidity decreases the current option price and predicts higher expected option returns. This effect is statistically and...

This chapter surveys the methods available for extracting forward-looking information from option prices. We consider volatility, skewness, kurtosis, and density forecasting. More generally, we discuss how any forecasting object which is a twice differentiable function of the future realization...