In this paper, we provide an exact particle filtering and parameter learning algorithm. Our approach exactly samples from a particle approximation to the joint posterior distribution of both parameters and latent states, thus avoiding the use of and the degeneracies inherent to sequential...

This paper studies the returns from investing in index options. Previous research documents significant average option returns, large CAPM alphas, and high Sharpe ratios, and concludes that put options are mispriced. We propose an alternative approach to evaluate the significance of option...

In this paper, we analyze the statistical and economic impact of earnings announcements on individual equity option prices. We develop no-arbitrage option pricing models in the presence of earnings announcements; we nonparametrically test for the importance of earnings announcements on option...

This paper examines specification issues and estimates volatility and jump risk premia using the information in the cross-section of Samp;P futures options from 1987 to 2003. We first test for the presence of jumps in volatility by analyzing the higher moment behavior of option implied variance,...

This chapter develops Markov Chain Monte Carlo (MCMC) methods for Bayesian inference in continuous-time asset pricing models. The Bayesian solution to the inference problem is the distribution of parameters and latent variables conditional on observed data, and MCMC methods provide a tool for...

Interest rate swap pricing theory traditionally views swaps as portfolios of forward contracts with net swap payments discounted using the LIBOR curve. Current market practices of marking-to-market and collateralization question this view. Collateralization and marking-to-market affects...

In this paper, we develop an approach for filtering state variables in the setting of continuous-time jump-diffusion models. Our method computes the filtering distribution of latent state variables conditional only on discretely observed observations in a manner consistent with the underlying...

This paper studies the economic benefits of return predictability by analyzing the impact of market and volatility timing on the performance of optimal portfolio rules. Using a model with time-varying expected returns and volatility, we form optimal portfolios sequentially and generate...

This paper examines a class of continuous-time models that incorporate jumps in returns and volatility, in addition to diffusive stochastic volatility. We develop a likelihood-based estimation strategy and provide estimates of model parameters, spot volatility, jump times and jump sizes using...

This paper provides an empirical analysis of the role of jumps in continuous-time models of the short rate. A diagnostic is developed to relate the failure of single and certain multi-factor models to the presence of unaccounted for jump-type movements. I introduce a nonparametric jump-diffusion...