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Benchmarking mean-variance portfolios using a shortage function : the choice of direction vector affects rankings !

Author

Listed:
  • K. Kerstens

    (LEM - Lille - Economie et Management - Université de Lille, Sciences et Technologies - CNRS - Centre National de la Recherche Scientifique)

  • A. Mounir
  • I. van de Woestyne
Abstract
In addition to its use in data envelopment analysis models, the shortage function has been proposed as a tool to gauge performance in multi-moment portfolio models. An open issue is how the choice of direction vector affects the efficiency measurement, especially when some of the data can be negative and, from a practical point of view, whether and how the resulting league tables are affected. This paper illustrates empirically how the choice of direction vector affects the relative ranking of mean-variance portfolios. This result is relevant to all frontier-based applications, especially those where some of the data can be naturally negative.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • K. Kerstens & A. Mounir & I. van de Woestyne, 2012. "Benchmarking mean-variance portfolios using a shortage function : the choice of direction vector affects rankings !," Post-Print hal-00728318, HAL.
    • Handle: RePEc:hal:journl:hal-00728318
    DOI: 10.1057/jors.2011.140
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    Cited by:

    1. Farshad Noravesh & Kristiaan Kerstens, 2022. "Some connections between higher moments portfolio optimization methods," Papers 2201.00205, arXiv.org.
    2. Paulo Matos & Guilherme Padilha & Maurício Benegas, 2016. "On the management efficiency of Brazilian stock mutual funds," Operational Research, Springer, vol. 16(3), pages 365-399, October.
    3. Briec, Walter & Dumas, Audrey & Kerstens, Kristiaan & Stenger, Agathe, 2022. "Generalised commensurability properties of efficiency measures: Implications for productivity indicators," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1481-1492.
    4. Cinzia Daraio & Léopold Simar, 2016. "Efficiency and benchmarking with directional distances: a data-driven approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(7), pages 928-944, July.

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