Robust Mean-Variance Hedging via G-Expectation

TL;DR

This paper develops a robust mean-variance hedging approach within the G-expectation framework, providing explicit strategies in a continuous market with model uncertainty, leveraging G-martingale representation theorems.

Contribution

It introduces a novel method for mean-variance hedging under G-expectation, explicitly computing optimal strategies for various contingent claims.

Findings

Explicit optimal hedging strategies derived.

Applicable to a broad class of contingent claims.

Utilizes G-martingale representation theorem effectively.

Abstract

In this paper we study mean-variance hedging under the G-expectation framework. Our analysis is carried out by exploiting the G-martingale representation theorem and the related probabilistic tools, in a contin- uous financial market with two assets, where the discounted risky one is modeled as a symmetric G-martingale. By tackling progressively larger classes of contingent claims, we are able to explicitly compute the optimal strategy under general assumptions on the form of the contingent claim.