Pairs selection and outranking: An application to the S&P 100 index

Abstract

Pairs trading is a popular quantitative speculation strategy. This article proposes a general and flexible framework for pairs selection. The method uses multiple return forecasts based on bivariate information sets and multi-criteria decision techniques. Our approach can be seen as a sort of forecast combination but the output of the method is a ranking. It helps to detect potentially under- and overvalued stocks. A first application with S&P 100 index stocks provides promising results in terms of excess return and directional forecasting. © 2008 Elsevier B.V. All rights reserved.