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...

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...

The main goal of this paper is to study the cross-sectional pricing of market volatility. The paper proposes that the market return, the diffusion volatility, and the jump volatility are fundamental factors that change the investors' investment opportunity set. Based on estimates of the...