Gain-probability diagrams as an alternative to significance testing in economics and finance

Abstract

PurposeThe purpose of this article is to show the gains that can be made if researchers were to use gain-probability (G-P) diagrams. Design/methodology/approachThe authors present relevant mathematical equations, invented examples and real data examples.FindingsG-P diagrams provide a more nuanced understanding of the data than typical summary statistics, effect sizes or significance tests.Practical implicationsGain-probability diagrams provided a much better basis for making decisions than typical summary statistics, effect sizes or significance tests.Originality/valueG-P diagrams provide a completely new way to traverse the distance from data to decision-making implications.