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Technical Note: Longitudinal Performance Stratification---An Iterative Kolmogorov-Smirnov Approach


  • Timothy W. Ruefli

    () (Department of Management Science and Information Systems, Graduate School of Business and IC² Institute, University of Texas at Austin, Austin, Texas 78712)

  • Robert R. Wiggins

    () (A.B. Freeman School of Business, Tulane University, McAlister Drive, New Orleans, Louisiana 70118-5669)


The stratification of entities into statistically distinct levels of performance over time is a problem encountered in a number of research and management settings. Traditional techniques to address this issue (e.g., cluster analysis) often require, either ex ante or ex post, the exogenous specification 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 different performance strata on a longitudinal basis. Monte Carlo simulations compare the new methodology with traditional clustering techniques. An application that stratifies mutual funds by returns illustrates the technique.

Suggested Citation

  • Timothy W. Ruefli & Robert R. Wiggins, 2000. "Technical Note: Longitudinal Performance Stratification---An Iterative Kolmogorov-Smirnov Approach," Management Science, INFORMS, vol. 46(5), pages 685-692, May.
  • Handle: RePEc:inm:ormnsc:v:46:y:2000:i:5:p:685-692

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    References listed on IDEAS

    1. Timothy W. Ruefli & Robert R. Wiggins, 1994. "When Mean Square Error Becomes Variance: A Comment on "Business Risk and Return: A Test of Simultaneous Relationships"," Management Science, INFORMS, vol. 40(6), pages 750-759, June.
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    Cited by:

    1. Emili Grifell-Tatjé & P. Marquès-Gou, 2002. "Measuring Sustained Superior Performance at the Firm Level," Working Papers 0208, Departament Empresa, Universitat Autònoma de Barcelona, revised Jul 2002.


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