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Omega portfolio models with floating return threshold

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  • Yu, Jing-Rung
  • Paul Chiou, Wan-Jiun
  • Hsin, Yi-Ting
  • Sheu, Her-Jiun

Abstract

The Omega ratio is a risk-performance measure that specifies the upside profit and the downside loss by giving a return threshold (τ). Since there is no clear specification for the return threshold, this study advances the Omega models by incorporating various settings of the return threshold that reflect market dynamics: (1) the yields of Treasury securities, and (2) the negative CVaR value (or the gain) generated from equity markets. To ensure the practicality, our models consider the transaction costs and short selling. The empirical results that apply the two asset classes to rebalance portfolios over 17 and 20 years suggest that using the floating τ values, particularly the Treasury rates, realize higher out-of-the-sample performance and less downside loss. Our proposed approach is practical as the benchmark rates in fixed-income markets can be easily observed. The major findings hold for both non-robust and robust portfolio models. The tests of various preferences between seeking profit and controlling loss (δ) confirm robustness of the major conclusion.

Suggested Citation

  • Yu, Jing-Rung & Paul Chiou, Wan-Jiun & Hsin, Yi-Ting & Sheu, Her-Jiun, 2022. "Omega portfolio models with floating return threshold," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 743-758.
  • Handle: RePEc:eee:reveco:v:82:y:2022:i:c:p:743-758
    DOI: 10.1016/j.iref.2022.08.018
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    1. Zakamouline, Valeri & Koekebakker, Steen, 2009. "Portfolio performance evaluation with generalized Sharpe ratios: Beyond the mean and variance," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1242-1254, July.
    2. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    3. C. Atkinson & S. Mokkhavesa, 2004. "Multi-asset portfolio optimization with transaction cost," Applied Mathematical Finance, Taylor & Francis Journals, vol. 11(2), pages 95-123.
    4. Branger, Nicole & Larsen, Linda Sandris & Munk, Claus, 2013. "Robust portfolio choice with ambiguity and learning about return predictability," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1397-1411.
    5. Michael R. Metel & Traian A. Pirvu & Julian Wong, 2017. "Risk Management under Omega Measure," Risks, MDPI, vol. 5(2), pages 1-14, May.
    6. Caporin, Massimiliano & Costola, Michele & Jannin, Gregory & Maillet, Bertrand, 2018. "“On the (Ab)use of Omega?”," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 11-33.
    7. Manfred GILLI & Enrico SCHUMANN & Giacomo DI TOLLO & Gerda CABEJ, 2008. "Constructing Long/Short Portfolios with the Omega ratio," Swiss Finance Institute Research Paper Series 08-34, Swiss Finance Institute.
    8. Yu, Jing-Rung & Lee, Wen-Yi, 2011. "Portfolio rebalancing model using multiple criteria," European Journal of Operational Research, Elsevier, vol. 209(2), pages 166-175, March.
    9. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    10. Fusai, Gianluca & Luciano, Elisa, 2001. "Dynamic value at risk under optimal and suboptimal portfolio policies," European Journal of Operational Research, Elsevier, vol. 135(2), pages 249-269, December.
    11. Laurent El Ghaoui & Maksim Oks & Francois Oustry, 2003. "Worst-Case Value-At-Risk and Robust Portfolio Optimization: A Conic Programming Approach," Operations Research, INFORMS, vol. 51(4), pages 543-556, August.
    12. Angelelli, Enrico & Mansini, Renata & Speranza, M. Grazia, 2008. "A comparison of MAD and CVaR models with real features," Journal of Banking & Finance, Elsevier, vol. 32(7), pages 1188-1197, July.
    13. Shushang Zhu & Masao Fukushima, 2009. "Worst-Case Conditional Value-at-Risk with Application to Robust Portfolio Management," Operations Research, INFORMS, vol. 57(5), pages 1155-1168, October.
    14. Gregory, Christine & Darby-Dowman, Ken & Mitra, Gautam, 2011. "Robust optimization and portfolio selection: The cost of robustness," European Journal of Operational Research, Elsevier, vol. 212(2), pages 417-428, July.
    15. Yusif Simaan, 1997. "Estimation Risk in Portfolio Selection: The Mean Variance Model Versus the Mean Absolute Deviation Model," Management Science, INFORMS, vol. 43(10), pages 1437-1446, October.
    16. Guastaroba, G. & Mansini, R. & Ogryczak, W. & Speranza, M.G., 2016. "Linear programming models based on Omega ratio for the Enhanced Index Tracking Problem," European Journal of Operational Research, Elsevier, vol. 251(3), pages 938-956.
    17. A. Ben-Tal & A. Nemirovski, 1998. "Robust Convex Optimization," Mathematics of Operations Research, INFORMS, vol. 23(4), pages 769-805, November.
    18. Amita Sharma & Sebastian Utz & Aparna Mehra, 2017. "Omega-CVaR portfolio optimization and its worst case analysis," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(2), pages 505-539, March.
    19. Kapsos, Michalis & Christofides, Nicos & Rustem, Berç, 2014. "Worst-case robust Omega ratio," European Journal of Operational Research, Elsevier, vol. 234(2), pages 499-507.
    20. Karthik Natarajan & Dessislava Pachamanova & Melvyn Sim, 2008. "Incorporating Asymmetric Distributional Information in Robust Value-at-Risk Optimization," Management Science, INFORMS, vol. 54(3), pages 573-585, March.
    21. Michael R. Metel & Traian A. Pirvu & Julian Wong, 2015. "Risk management under Omega measure," Papers 1510.05790, arXiv.org, revised Apr 2017.
    22. Huang, Dashan & Zhu, Shushang & Fabozzi, Frank J. & Fukushima, Masao, 2010. "Portfolio selection under distributional uncertainty: A relative robust CVaR approach," European Journal of Operational Research, Elsevier, vol. 203(1), pages 185-194, May.
    23. M. Gilli & E. Kellezi & H. Hysi, 2006. "A Data-Driven Optimization Heuristic for Downside Risk Minimization," Computing in Economics and Finance 2006 355, Society for Computational Economics.
    24. Takeda, Akiko & Kanamori, Takafumi, 2009. "A robust approach based on conditional value-at-risk measure to statistical learning problems," European Journal of Operational Research, Elsevier, vol. 198(1), pages 287-296, October.
    25. Woodside-Oriakhi, M. & Lucas, C. & Beasley, J.E., 2013. "Portfolio rebalancing with an investment horizon and transaction costs," Omega, Elsevier, vol. 41(2), pages 406-420.
    26. Hiroshi Konno & Hiroaki Yamazaki, 1991. "Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market," Management Science, INFORMS, vol. 37(5), pages 519-531, May.
    27. Kolm, Petter N. & Tütüncü, Reha & Fabozzi, Frank J., 2014. "60 Years of portfolio optimization: Practical challenges and current trends," European Journal of Operational Research, Elsevier, vol. 234(2), pages 356-371.
    28. Michael J. Best & Robert R. Grauer, 1991. "Sensitivity Analysis for Mean-Variance Portfolio Problems," Management Science, INFORMS, vol. 37(8), pages 980-989, August.
    29. Bernd Scherer, 2007. "Can robust portfolio optimisation help to build better portfolios?," Journal of Asset Management, Palgrave Macmillan, vol. 7(6), pages 374-387, March.
    30. Quaranta, Anna Grazia & Zaffaroni, Alberto, 2008. "Robust optimization of conditional value at risk and portfolio selection," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2046-2056, October.
    31. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
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