A Harris process to model stochastic volatility

A tractable non-independent increment process is presented. The process arises as an extension of the so-called Harris chains to continuous time being stationary and Feller. Constructions, properties, and inference methods are explored. Moreover, the process is used to propose a stochastic volatility model with an arbitrary but fixed invariant distribution which can be tailored to fit different applied scenarios. The model performance is studied through simulation while illustrating its use in practice with empirical work. The model proves to be an interesting competitor to a number of short-range stochastic volatility models.