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Portfolio Construction and Performance Measurement when Returns are Non-Normal

Author

Listed:
  • Karen Benson

    (UQ Business School, The University of Queensland, St Lucia, QLD 4072.)

  • Philip Gray

    (UQ Business School, The University of Queensland, St Lucia, QLD 4072.)

  • Egon Kalotay

    (Department of Accounting and Finance, Macquarie University.)

  • Judy Qiu

    (UQ Business School, The University of Queensland, St Lucia, QLD 4072.)

Abstract

The foundation of popular approaches to portfolio construction and performance measurement lies in the mean-variance framework of Markowitz (1952, 1959). However, the suitability of such approaches in practice is questionable in light of considerable evidence of non-normalities in returns. This paper explores the potential usefulness of a non-parametric approach to portfolio construction and performance measurement recently proposed by Stutzer (2000). The Portfolio Performance Index (PPI) is based on the notion that investors associate risk with the failure to achieve a target return. Stutzer proposes that portfolio construction and performance measurement be approached by calculating the decay rate in the probability that a given portfolio will underperform its designated benchmark. By comparing the PPI and Sharpe ratio metrics, this paper presents preliminary evidence of the economic significance of non-normalities in Australian equity returns, and documents the impact of such on portfolio construction and performance evaluation practice.

Suggested Citation

  • Karen Benson & Philip Gray & Egon Kalotay & Judy Qiu, 2008. "Portfolio Construction and Performance Measurement when Returns are Non-Normal," Australian Journal of Management, Australian School of Business, vol. 32(3), pages 445-461, March.
  • Handle: RePEc:sae:ausman:v:32:y:2008:i:3:p:445-461
    DOI: 10.1177/031289620803200304
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    References listed on IDEAS

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    1. Henriksson, Roy D & Merton, Robert C, 1981. "On Market Timing and Investment Performance. II. Statistical Procedures for Evaluating Forecasting Skills," The Journal of Business, University of Chicago Press, vol. 54(4), pages 513-533, October.
    2. Michael Stutzer, 2011. "Portfolio choice with endogenous utility: a large deviations approach," World Scientific Book Chapters, in: Leonard C MacLean & Edward O Thorp & William T Ziemba (ed.), THE KELLY CAPITAL GROWTH INVESTMENT CRITERION THEORY and PRACTICE, chapter 43, pages 619-640, World Scientific Publishing Co. Pte. Ltd..
    3. Sawicki, Julia & Ong, Fred, 2000. "Evaluating managed fund performance using conditional measures: Australian evidence," Pacific-Basin Finance Journal, Elsevier, vol. 8(3-4), pages 505-528, July.
    4. Ferson, Wayne E & Schadt, Rudi W, 1996. "Measuring Fund Strategy and Performance in Changing Economic Conditions," Journal of Finance, American Finance Association, vol. 51(2), pages 425-461, June.
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    Cited by:

    1. Rand Kwong Yew Low, 2018. "Vine copulas: modelling systemic risk and enhancing higher‐moment portfolio optimisation," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 423-463, November.
    2. Jun Jiang, 2013. "Application of Modern Portfolio Theory In The Case Of Thai Equity Market," International Journal of Empirical Finance, Research Academy of Social Sciences, vol. 1(2), pages 33-42.

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