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Simple and cross efficiency of CTAs using data envelopment analysis

Author

Listed:
  • Greg Gregoriou
  • Fabrice Rouah
  • Stephen Satchell
  • Fernando Diz

Abstract

Data envelopment analysis (DEA) is applied, and basic and cross-efficiency models are used to evaluate the performance of CTA classifications. With the ever-increasing number of CTAs, there is an urgent requirement to provide money managers, pension funds, and high-net-worth individuals with a trustworthy appraisal method in ranking their efficiency. DEA can achieve this, and one important benefit of this measure is that benchmarks are not required, thereby alleviating the problem of using traditional benchmarks to examine non-normal returns. This article aims to investigate CTAs and to identify the ones that have achieved superior performance or, in other words, have an efficiency score of 100 in a risk/return setting.

Suggested Citation

  • Greg Gregoriou & Fabrice Rouah & Stephen Satchell & Fernando Diz, 2005. "Simple and cross efficiency of CTAs using data envelopment analysis," The European Journal of Finance, Taylor & Francis Journals, vol. 11(5), pages 393-409.
  • Handle: RePEc:taf:eurjfi:v:11:y:2005:i:5:p:393-409
    DOI: 10.1080/1351847042000286667
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    References listed on IDEAS

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    1. Basso, Antonella & Funari, Stefania, 2001. "A data envelopment analysis approach to measure the mutual fund performance," European Journal of Operational Research, Elsevier, vol. 135(3), pages 477-492, December.
    2. Richard S. BARR & Lawrence M. SEIFORD & Thomas F. SIEMS, 1994. "Forecasting Bank Failure : A Non-Parametric Frontier Estimation Approach," Discussion Papers (REL - Recherches Economiques de Louvain) 1994041, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    3. A. Charnes & W. W. Cooper & E. Rhodes, 1981. "Evaluating Program and Managerial Efficiency: An Application of Data Envelopment Analysis to Program Follow Through," Management Science, INFORMS, vol. 27(6), pages 668-697, June.
    4. Muhittin Oral & Ossama Kettani & Pascal Lang, 1991. "A Methodology for Collective Evaluation and Selection of Industrial R&D Projects," Management Science, INFORMS, vol. 37(7), pages 871-885, July.
    5. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    6. Morey, Matthew R. & Morey, Richard C., 1999. "Mutual fund performance appraisals: a multi-horizon perspective with endogenous benchmarking," Omega, Elsevier, vol. 27(2), pages 241-258, April.
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    Cited by:

    1. Lamb, John D. & Tee, Kai-Hong, 2012. "Data envelopment analysis models of investment funds," European Journal of Operational Research, Elsevier, vol. 216(3), pages 687-696.
    2. Jacques Pézier, 2011. "Rationalization of Investment Preference Criteria," ICMA Centre Discussion Papers in Finance icma-dp2011-12, Henley Business School, Reading University.
    3. repec:eee:jomega:v:75:y:2018:i:c:p:57-76 is not listed on IDEAS
    4. repec:pal:jorsoc:v:59:y:2008:i:10:d:10.1057_palgrave.jors.2602462 is not listed on IDEAS
    5. Tarnaud, Albane Christine & Leleu, Hervé, 2018. "Portfolio analysis with DEA: Prior to choosing a model," Omega, Elsevier, vol. 75(C), pages 57-76.
    6. Glawischnig, Markus & Sommersguter-Reichmann, Margit, 2010. "Assessing the performance of alternative investments using non-parametric efficiency measurement approaches: Is it convincing?," Journal of Banking & Finance, Elsevier, vol. 34(2), pages 295-303, February.

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