StochasticDominance.jl: A Julia Package for Higher Order Stochastic Dominance

TL;DR

The paper introduces StochasticDominance.jl, a Julia package that simplifies the application of higher-order stochastic dominance constraints in decision-making and finance by reducing computational complexity.

Contribution

It presents an open-source Julia package that efficiently verifies and optimizes under higher-order stochastic dominance constraints, based on recent theoretical reductions.

Findings

Enables practical application of higher-order stochastic dominance

Reduces infinite constraints to finite, manageable numbers

Provides a user-friendly, black-box optimization tool

Abstract

Stochastic dominance is a fundamental concept in decision-making under uncertainty and quantitative finance, yet its practical application is hindered by computational intractability due to infinitely many constraints. We introduce the Julia package StochasticDominance, an open-source tool that efficiently verifies and optimizes under higher-order stochastic dominance constraints. Our approach builds on recent theoretical advancements that reduce infinite constraints to a finite number, making higher-order stochastic dominance more accessible. This package provides a user-friendly, black-box solution, enabling researchers and practitioners to incorporate stochastic dominance constraints seamlessly into their optimization frameworks.