Superhedging under Proportional Transaction Costs in Continuous Time

TL;DR

This paper develops a dynamic, set-valued approach to superhedging under proportional transaction costs in continuous time, introducing new mathematical tools and approximate strategies to better understand and compute superhedging sets.

Contribution

It introduces a set-valued stochastic analysis framework for superhedging, including dynamic superhedging sets, their properties, and approximate versions with a set-valued Bellman's principle.

Findings

Superhedging sets form a dynamic set-valued risk measure.

Approximate superhedging sets relate through a set-valued Bellman's principle.

The approach paves the way for a set-valued differential structure.

Abstract

We revisit the well-studied superhedging problem under proportional transaction costs in continuous time using the recently developed tools of set-valued stochastic analysis. By relying on a simple Black-Scholes-type market model for mid-prices and using continuous trading schemes, we define a dynamic family of superhedging sets in continuous time and express them in terms of set-valued integrals. We show that these sets, defined as subsets of Lebesgue spaces at different times, form a dynamic set-valued risk measure with multi-portfolio time-consistency. Finally, we transfer the problem formulation to a path-space setting and introduce approximate versions of superhedging sets that will involve relaxing the superhedging inequality, the superhedging probability, and the solvency requirement for the superhedging strategy with a predetermined error level. In this more technical framework, we are able to relate the approximate superhedging sets at different times by means of a set-valued Bellman's principle, which we believe will pave the way for a set-valued differential structure that characterizes the superhedging sets.