The transformed-data maximum likelihood estimation (MLE) method for struc- tural credit risk models developed by Duan (1994) is extended to account for the fact that observed equity prices may have been contaminated by trading noises. With the presence of trading noises, the likelihood function...

We develop a new model where the dynamic structure of the asset price, after the fundamental value is removed, is subject to two different regimes. One regime reflects the normal period where the asset price divided by the dividend is assumed to follow a mean-reverting process around a...

The paper proposes a self-exciting asset pricing model that takes into account co-jumps between prices and volatility and self-exciting jump clustering. We employ a Bayesian learning approach to implement real time sequential analysis. We find evidence of self-exciting jump clustering since the...

In dynamic asset pricing models, when the model structure becomes complex and derivatives data are introduced in estimation, traditional Bayesian MCMC methods converge slowly, are difficult to design efficient proposals for parameters, and have large computational cost. We propose a two-stage...

We develop a new model where the dynamic structure of the asset price, after the fundamental value is removed, is subject to two different regimes. One regime reflects the normal period where the asset price divided by the dividend is assumed to follow a mean-reverting process around a...

Relying on a latent factor model with time-varying temporal dependence of systematic risk and mispricing on firm and option characteristics, we reveal economically substantial mispricing in the options market. The portfolio based on individual options alphas related to characteristics earns an...