Distributionally robust profit opportunities

Derek Singh, Shuzhong Zhang

Research output: Contribution to journalArticlepeer-review

Abstract

This paper expands the notion of robust profit opportunities in financial markets to incorporate distributional ambiguity 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 distributional ambiguity helps or hurts 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.

Original languageEnglish (US)
Pages (from-to)121-128
Number of pages8
JournalOperations Research Letters
Volume49
Issue number1
DOIs
StatePublished - Jan 2021

Bibliographical note

Publisher Copyright:
© 2020 Elsevier B.V.

Keywords

  • Distributionally robust optimization
  • Lagrangian duality
  • Robust profit opportunities
  • Sharpe ratio
  • Wasserstein distance

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