A new stochastic dominance criterion for dependent random variables with applications

TL;DR

This paper introduces a novel stochastic dominance criterion that accounts for dependence between variables, offering a more nuanced comparison method especially useful for paired data and asset returns.

Contribution

The paper develops a new stochastic dominance criterion that incorporates dependence structure, improving upon traditional methods that ignore such dependencies.

Findings

Provides a detailed comparison of dependent random variables.

Overcomes limitations of Student's t and Wilcoxon tests for non-normal data.

Applicable to asset return comparisons.

Abstract

In this paper we develop a new tool for the comparison of paired data based on a new criterion of stochastic dominance that takes into account the dependence structure of the random variables under comparison. This new procedure provides a more detailed comparison of dependent random variables and overcomes some difficulties of standard techniques like Student's t and Wilcoxon-Mann-Whitney tests for non normal data. This tool provides an alternative to the usual stochastic dominance criterion which only considers the marginal distributions in the comparison. We show how this new tool can be fruitfully used for the comparison of paired asset returns.