Which loss function should be used when estimating and evaluating option valuation models? Many different functions have been suggested, but no standard has emerged. We do not promote a particular function, but instead emphasize that consistency in the choice of loss functions is crucial. First,...

We consider three sets of phenomena that feature prominently - and separately - in the financial economics literature: conditional mean dependence (or lack thereof) in asset returns, dependence (and hence forecastability) in asset return signs with implications for market timing, and dependence...

Characterizing asset return dynamics using GARCH models is an important part of empirical finance. The existing literature favors some rather complex volatility specifications whose relative performance is usually assessed through their likelihood based on a time-series of asset returns. This...

It depends. If volatility fluctuates in a forecastable way, then volatility forecasts are useful for risk management; hence the interest in volatility forecastability in the risk management literature. Volatility forecastability, however, varies with horizon, and different horizons are relevant...

We build a new class of discrete time models where the distribution of daily returns is driven by two factors: dynamic volatility and dynamic jump intensity. Each factor has its own risk premium. The likelihood function for the models is available using analytical filtering, which makes them...

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...

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...

When the relationship between observed fixed-income securities and the latent state variables in dynamic term structure models is nonlinear, existing studies usually linearize this relationship because nonlinear filtering is computationally demanding. We propose the use of the unscented Kalman...

Both large oil price increases and decreases are associated with deteriorating economic conditions. Consistent with this stylized fact, we find that the projection of the state price density (SPD) on oil returns estimated from oil futures and option prices displays a U-shaped pattern. Because...

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...