Martingale Problem under Nonlinear Expectations

TL;DR

This paper extends the classical martingale problem framework to nonlinear expectation spaces, introducing new methods to handle fully nonlinear PDEs and establishing existence of weak solutions without requiring measure absolute continuity.

Contribution

It formulates and solves the martingale problem under nonlinear expectations, defining weak solutions and proving their existence without the need for measure absolute continuity.

Findings

Established a framework for martingale problems in nonlinear expectation spaces.

Proved existence of weak solutions under H"older continuity of coefficients.

Generalized Girsanov transformation to nonlinear settings.

Abstract

We formulate and solve the martingale problem in a nonlinear expectation space. Unlike the classical work of Stroock and Varadhan (1969) where the linear operator in the associated PDE is naturally defined from the corresponding diffusion process, the main difficulty in the nonlinear setting is to identify an appropriate class of nonlinear operators for the associated fully nonlinear PDEs. Based on the analysis of the martingale problem, we introduce the notion of weak solution for stochastic differential equations under nonlinear expectations and obtain an existence theorem under the H\"older continuity condition of the coefficients. The approach to establish the existence of weak solutions generalizes the classical Girsanov transformation method in that it no longer requires the two (probability) measures to be absolutely continuous.