Distributionally Robust Profit Opportunities

TL;DR

This paper investigates how distributional uncertainty, measured via Wasserstein distance, affects the robustness of profit opportunities in financial markets, providing theoretical insights and computational experiments.

Contribution

It introduces a framework incorporating distributional ambiguity into profit opportunity analysis using Wasserstein distance, with dual problem formulation and empirical evaluation.

Findings

Distributional uncertainty can both enhance and diminish profit robustness.

Finite dimensional dual problems simplify the analysis of infinite dimensional primal problems.

Theoretical results are supported by computational experiments.

Abstract

This paper expands the notion of robust profit opportunities in financial markets to incorporate distributional uncertainty using Wasserstein distance as the ambiguity measure. Financial markets with risky and risk-free assets are considered. The infinite dimensional primal problems are formulated, leading to their simpler finite dimensional dual problems. A principal motivating question is how does distributional uncertainty help or hurt the robustness of the profit opportunity. Towards answering this question, some theory is developed and computational experiments are conducted. Finally some open questions and suggestions for future research are discussed.