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

We introduce a top-down no-arbitrage model for pricing structured products. The losses are described by Cox processes whose intensities depend on economic variables. The model provides economic insight into the impact of structured products on the risk exposure of financial institutions and...

The computational cost of estimating option valuation models is very high, due to model complexity and the abundance of available option data. We propose an approach that addresses these computational constraints by filtering the state variables using particle weights based on model-implied spot...

Options on crude oil futures are the most actively traded commodity options. We develop a class of computationally efficient discrete-time jump models that allow for closed-form option valuation, and we use crude oil futures and options data to investigate the economic importance of jumps and...

Several papers have questioned the ability of multifactor affine models to extract interest rate volatility from the cross-section of bond prices. These studies find that the conditional volatility implied by these models is very poorly or even negatively correlated with model-free volatility....

We show that option-implied tail risk plays an important role in understanding the risk premium around FOMC announcement days. We construct abnormal option-implied moments before each pre-scheduled FOMC meeting. While volatility predicts pre-FOMC drift and the announcement day market returns,...

We use intraday data to compute weekly realized variance, skewness, and kurtosis for equity returns and study the realized moments' time-series and cross-sectional properties. We investigate if this week's realized moments are informative for the cross-section of next week's stock returns. We...

This paper investigates the importance of market incompleteness by comparing the rates of risk aversion estimated from complete and incomplete markets environments. For the incomplete-markets case, we use consumption data for the 50 US states. We find that the rate of risk aversion under the...

International equity markets are characterized by nonlinear dependence and asymmetries. We propose a new dynamic asymmetric copula model to capture long-run and short-run dependence, multivariate nonnormality, and asymmetries in large cross-sections. We find that copula correlations have...

The extended Kalman filter, which linearizes the relationship between security prices and state variables, is widely used in fixed income applications. We investigate if the unscented Kalman filter should be used to capture nonlinearities, and compare the performance of the Kalman filter to that...