Feller Processes: The Next Generation in Modeling. Brownian Motion, L\'evy Processes and Beyond

TL;DR

This paper introduces a new construction method for Feller processes, enabling the generation of sample paths and facilitating Monte Carlo simulations for spatially inhomogeneous stochastic processes.

Contribution

It provides a simple, practical framework for constructing and simulating Feller processes, extending the capabilities beyond traditional Le9vy processes and Brownian motion.

Findings

Framework for generating sample paths of Feller processes

Simulation technique enabling Monte Carlo methods

Extension of stochastic modeling to spatially inhomogeneous processes

Abstract

We present a simple construction method for Feller processes and a framework for the generation of sample paths of Feller processes. The construction is based on state space dependent mixing of L\'evy processes. Brownian Motion is one of the most frequently used continuous time Markov processes in applications. In recent years also L\'evy processes, of which Brownian Motion is a special case, have become increasingly popular. L\'evy processes are spatially homogeneous, but empirical data often suggest the use of spatially inhomogeneous processes. Thus it seems necessary to go to the next level of generalization: Feller processes. These include L\'evy processes and in particular Brownian motion as special cases but allow spatial inhomogeneities. Many properties of Feller processes are known, but proving the very existence is, in general, very technical. Moreover, an applicable framework for the generation of sample paths of a Feller process was missing. We explain, with practitioners in mind, how to overcome both of these obstacles. In particular our simulation technique allows to apply Monte Carlo methods to Feller processes.