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Statistical Inference and Efficient Portfolio Investment Performance

Author

Listed:
  • Shibo Liu

    (School of Business and Economics, Loughborough University)

  • Tom Weyman-Jones

    (School of Business and Economics, Loughborough University)

  • Karligash Glass

    (School of Business and Economics, Loughborough University)

Abstract

The original Morey and Morey (1999) paper was the first to explicitly link the efficient theoretical frontier of the Markowitz portfolio balance model to the concept of the efficient empirical frontier in data envelopment analysis. The contribution of this paper is to extend the application of this linked research strategy to incorporate both sampling error addressed through bootstrapping and contextual explanation of the efficiency results through statistically robust second stage analysis. This paper first applies the procedures in Morey and Morey (1999) to a new modern data set comprising a multi-year sample of investment funds and then utilises Simar-Wilson (2008) bootstrapping algorithms to develop statistical inference and confidence intervals for the indexes of efficient investment fund performance. For the second stage analysis, robust-OLS regression, Tobit models and Papke-Wooldridge (PW) models are conducted and compared to evaluate contextual variables affecting the performance of investment funds.

Suggested Citation

  • Shibo Liu & Tom Weyman-Jones & Karligash Glass, 2015. "Statistical Inference and Efficient Portfolio Investment Performance," Discussion Paper Series 2015_01, Department of Economics, Loughborough University, revised Jan 2015.
    • Handle: RePEc:lbo:lbowps:2015_01
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    File URL: http://www.lboro.ac.uk/departments/sbe/RePEc/lbo/lbowps/Liu_TW-J_KGlass_WP2015_01.pdf
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    More about this item

    Keywords

    nonlinear-DEA; portfolios; bootstrapping; second stage DEA;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • G1 - Financial Economics - - General Financial Markets
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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