This paper analyzes the Shot-Noise Jump-Diffusion model of Altmann, Schmidt and Stute (2008), which
introduces a new situation where the effects of the arrival of rare, shocking information to the financial
markets may fade away in the long run. We analyze several economic implications of the model,
providing an analytical expression for the process distribution. We also prove that certain specifications
of this model can provide negative serial persistence. Additionally, we find that the degree of serial
autocorrelation is related to the arrival and magnitude of abnormal information. Finally, a GMM
framework is proposed to estimate the model parameters
