We propose a nonparametric estimation technique of the coefficients of an univariate diffusion process. The estimation is done with a process observed at random times, corresponding to the crossing times of discrete levels. We first estimate the scale function of the process, which allows to...

We study inference in continuous and discrete processes and propose new estimation procedures. Our approach consists on truncating the initial process what simplifies the estimation while preventing all relevant properties of the infinitesimal generator. For diffusion processes, nonparametric...

We consider truncated processes, both in discrete and continuous time, and study their dynamic properties. When the underlying process is a diffusion process, we derive the infinitesimal generator of its truncated counterpart. This result is the basis for the estimation of the drift and...