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Upside Beta Ratio: A Performance Measure For Potential-Seeking Investors

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  • DIPANKAR MONDAL

    (Department of Mathematics, Indian Institute of Technology Guwahati, Guwahati 781039, India)

  • N. SELVARAJU

    (Department of Mathematics, Indian Institute of Technology Guwahati, Guwahati 781039, India)

Abstract

This paper proposes a set of desirable axioms to characterize performance measures in the context of portfolio management. A performance measure consistent with the axioms is called “ideal”. We observe that a popular performance measure, Farinelli–Tibiletti (FT) ratio [S. Farinelli & L. Tibiletti (2008) Sharpe thinking in asset ranking with one-sided measures, European Journal of Operational Research 185 (3), 1542–1547], which captures potential-seeking behavior, is not ideal. It violates a very important property of portfolio theory, the diversification. As an alternative, we propose a new ideal performance measure, upside beta ratio (UBR). To examine its performance, we rank mutual funds for UBR and other four performance measures — Sharpe, Sortino, FT and Jensen’s alpha — and then we compare the rankings of UBR with the rankings of other ratios. In addition, the performance of top-ranked funds are compared through back-testing and out-of-sample analysis. Our findings reveal that the UBR performs significantly better than the other ratios in most scenarios. Finally, in order to check robustness of the new measure, a parameter sensitivity analysis is presented.

Suggested Citation

  • Dipankar Mondal & N. Selvaraju, 2020. "Upside Beta Ratio: A Performance Measure For Potential-Seeking Investors," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 23(02), pages 1-26, April.
  • Handle: RePEc:wsi:ijtafx:v:23:y:2020:i:02:n:s0219024920500144
    DOI: 10.1142/S0219024920500144
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    References listed on IDEAS

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    1. Farinelli, Simone & Tibiletti, Luisa, 2008. "Sharpe thinking in asset ranking with one-sided measures," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1542-1547, March.
    2. Dowd, Kevin, 2000. "Adjusting for risk:: An improved Sharpe ratio," International Review of Economics & Finance, Elsevier, vol. 9(3), pages 209-222, July.
    3. Massimiliano Caporin & Grégory M. Jannin & Francesco Lisi & Bertrand B. Maillet, 2014. "A Survey On The Four Families Of Performance Measures," Journal of Economic Surveys, Wiley Blackwell, vol. 28(5), pages 917-942, December.
    4. Martin R. Young, 1998. "A Minimax Portfolio Selection Rule with Linear Programming Solution," Management Science, INFORMS, vol. 44(5), pages 673-683, May.
    5. Holthausen, Duncan M, 1981. "A Risk-Return Model with Risk and Return Measured as Deviations from a Target Return," American Economic Review, American Economic Association, vol. 71(1), pages 182-188, March.
    6. R. Rockafellar & Stan Uryasev & Michael Zabarankin, 2006. "Generalized deviations in risk analysis," Finance and Stochastics, Springer, vol. 10(1), pages 51-74, January.
    7. Fishburn, Peter C, 1977. "Mean-Risk Analysis with Risk Associated with Below-Target Returns," American Economic Review, American Economic Association, vol. 67(2), pages 116-126, March.
    8. Vikas Agarwal, 2004. "Risks and Portfolio Decisions Involving Hedge Funds," The Review of Financial Studies, Society for Financial Studies, vol. 17(1), pages 63-98.
    9. Nawrocki, David & Viole, Fred, 2014. "Behavioral finance in financial market theory, utility theory, portfolio theory and the necessary statistics: A review," Journal of Behavioral and Experimental Finance, Elsevier, vol. 2(C), pages 10-17.
    10. Cumova, Denisa & Nawrocki, David, 2014. "Portfolio optimization in an upside potential and downside risk framework," Journal of Economics and Business, Elsevier, vol. 71(C), pages 68-89.
    11. Svetlozar Rachev & Sergio Ortobelli & Stoyan Stoyanov & Frank J. Fabozzi & Almira Biglova, 2008. "Desirable Properties Of An Ideal Risk Measure In Portfolio Theory," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 19-54.
    12. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    13. Antonio E. Bernardo & Olivier Ledoit, 2000. "Gain, Loss, and Asset Pricing," Journal of Political Economy, University of Chicago Press, vol. 108(1), pages 144-172, February.
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    1. Righi, Marcelo Brutti, 2024. "Star-shaped acceptability indexes," Insurance: Mathematics and Economics, Elsevier, vol. 117(C), pages 170-181.

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