Technical note: Longitudinal performance stratification - An iterative Kolmogorov-Smirnov approach

The stratification of entities into statistically distinct levels of perfor mance over time is a problem encountered in a number of research and manage ment settings. Traditional techniques to address this issue (e.g., cluster analysis) often require, either ex ante or ex post, the exogenous specifica tion of the number of groups to be employed in further analysis-and are not especially suited to dealing with distributions over time. The methodology presented here iteratively applies the Kolmogorov-Smirnov two-sample test to identify the number and membership of statistically significantly differ ent performance strata on a longitudinal basis. Monte Carlo simulations com pare the new methodology with traditional clustering techniques. An applica tion that stratifies mutual funds by returns illustrates the technique.