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Monotone Sharpe ratios and related measures of investment performance

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  • Mikhail Zhitlukhin

Abstract

We introduce a new measure of performance of investment strategies, the monotone Sharpe ratio. We study its properties, establish a connection with coherent risk measures, and obtain an efficient representation for using in applications.

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  • Mikhail Zhitlukhin, 2018. "Monotone Sharpe ratios and related measures of investment performance," Papers 1809.10193, arXiv.org, revised May 2021.
    • Handle: RePEc:arx:papers:1809.10193
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    1. Justin R. Davis & Stan Uryasev, 2016. "Analysis of tropical storm damage using buffered probability of exceedance," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(1), pages 465-483, August.
    2. PAVLO A. Krokhmal, 2007. "Higher moment coherent risk measures," Quantitative Finance, Taylor & Francis Journals, vol. 7(4), pages 373-387.
    3. Mafusalov, Alexander & Shapiro, Alexander & Uryasev, Stan, 2018. "Estimation and asymptotics for buffered probability of exceedance," European Journal of Operational Research, Elsevier, vol. 270(3), pages 826-836.
    4. Rockafellar, R.T. & Royset, J.O., 2010. "On buffered failure probability in design and optimization of structures," Reliability Engineering and System Safety, Elsevier, vol. 95(5), pages 499-510.
    5. Duan Li & Wan‐Lung Ng, 2000. "Optimal Dynamic Portfolio Selection: Multiperiod Mean‐Variance Formulation," Mathematical Finance, Wiley Blackwell, vol. 10(3), pages 387-406, July.
    6. Mikhail Zhitlukhin, 2016. "A Second-order Monotone Modification of the Sharpe Ratio," World Scientific Book Chapters, in: Masaaki Kijima & Yukio Muromachi & Takashi Shibata (ed.), RECENT ADVANCES IN FINANCIAL ENGINEERING 2014 Proceedings of the TMU Finance Workshop 2014, chapter 10, pages 217-226, World Scientific Publishing Co. Pte. Ltd..
    7. D. J. White, 1974. "Technical Note—Dynamic Programming and Probabilistic Constraints," Operations Research, INFORMS, vol. 22(3), pages 654-664, June.
    8. 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.
    9. Henry R. Richardson, 1989. "A Minimum Variance Result in Continuous Trading Portfolio Optimization," Management Science, INFORMS, vol. 35(9), pages 1045-1055, September.
    10. Patrick Cheridito & Tianhui Li, 2009. "Risk Measures On Orlicz Hearts," Mathematical Finance, Wiley Blackwell, vol. 19(2), pages 189-214, April.
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    Cited by:

    1. Marcelo Brutti Righi, 2021. "Star-shaped acceptability indexes," Papers 2110.08630, arXiv.org, revised Jun 2022.

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