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Portfolio Performance Gauging in Discrete Time Using a Luenberger Productivity Indicator

  • Olivier Brandouy

    (CNRS-LEM(UMR 8179),IAE,University of Lille 1)

  • Walter Briec

    (University of Perpignan, LAMPS)

  • Kristiaan Kerstens

    ()

    (CNRS-LEM (UMR 8179), IESEG School of Management)

  • Ignace Van de Woestyne

    (HUB University College Brussels)

This paper proposes a pragmatic, discrete time indicator to gauge the performance of portfolios over time. Integrating the shortage function (Luenberger, 1995) into a Luenberger portfolio productivity indicator (Chambers, 2002), this study estimates the changes in the relative positions of portfolios with respect to the traditional Markowitz mean-variance efficient frontier, as well as the eventual shifts of this frontier over time. Based on the analysis of local changes relative to these mean-variance and higher moment (in casu, mean-variance-skewness) frontiers, this methodology allows to neatly separate between on the one hand performance changes due to portfolio strategies and on the other hand performance changes due to the market evolution. This methodology is empirically illustrated using a mimicking portfolio approach (Fama and French 1996; 1997) using US monthly data from January 1931 to August 2007.

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Paper provided by IESEG School of Management in its series Working Papers with number 2008-ECO-12.

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Length: 27 pages
Date of creation: Oct 2008
Date of revision: Oct 2009
Handle: RePEc:ies:wpaper:e200812
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  1. William N. Goetzmann & Stephen J. Brown, 2005. "Performance Persistence," Yale School of Management Working Papers ysm451, Yale School of Management.
  2. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, 03.
  3. Eling, Martin & Schuhmacher, Frank, 2007. "Does the choice of performance measure influence the evaluation of hedge funds?," Journal of Banking & Finance, Elsevier, vol. 31(9), pages 2632-2647, September.
  4. Cuthbertson, Keith & Nitzsche, Dirk & O'Sullivan, Niall, 2008. "UK mutual fund performance: Skill or luck?," Journal of Empirical Finance, Elsevier, vol. 15(4), pages 613-634, September.
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  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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  12. Josef Lakonishok & Andrei Shleifer & Robert W. Vishny, 1993. "Contrarian Investment, Extrapolation, and Risk," University of Chicago - George G. Stigler Center for Study of Economy and State 84, Chicago - Center for Study of Economy and State.
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  18. Edwin J. Elton, 1999. "Presidential Address: Expected Return, Realized Return, and Asset Pricing Tests," Journal of Finance, American Finance Association, vol. 54(4), pages 1199-1220, 08.
  19. Fama, Eugene F & French, Kenneth R, 1996. " Multifactor Explanations of Asset Pricing Anomalies," Journal of Finance, American Finance Association, vol. 51(1), pages 55-84, March.
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  22. Russ Wermers, 2000. "Mutual Fund Performance: An Empirical Decomposition into Stock-Picking Talent, Style, Transactions Costs, and Expenses," Journal of Finance, American Finance Association, vol. 55(4), pages 1655-1703, 08.
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  29. Robert G. Chambers, 2002. "Exact nonradial input, output, and productivity measurement," Economic Theory, Springer, vol. 20(4), pages 751-765.
  30. Walter Briec & Kristiaan Kerstens & Octave Jokung, 2007. "Mean-Variance-Skewness Portfolio Performance Gauging: A General Shortage Function and Dual Approach," Management Science, INFORMS, vol. 53(1), pages 135-149, January.
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