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Refinements to the Sharpe ratio: Comparing alternatives for bear markets

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  • Hendrik Scholz

    (Ingolstadt School of Management, Catholic University of Eichstaett-Ingolstadt, Auf der Schanz 49)

Abstract

In recent years, various proposals have been published and discussed on overcoming the problems in evaluating fund performance based on ex post Sharpe ratios during periods of declining markets. In particular, it has frequently been debated whether negative Sharpe ratios, which naturally occur in bear markets, reliably measure fund performance. This paper presents refinements to the Sharpe ratio and compares them with the original Sharpe ratio. We show that only the so-called normalised Sharpe ratio produces meaningful results, not only for bear markets, but for any other market period as well. Our findings are derived from theoretical analyses based on a factor model and checked for plausibility against economic fundamentals. The practical relevance of our theoretical results is confirmed by a subsequent empirical study based on sample data from US equity mutual funds.

Suggested Citation

  • Hendrik Scholz, 2007. "Refinements to the Sharpe ratio: Comparing alternatives for bear markets," Journal of Asset Management, Palgrave Macmillan, vol. 7(5), pages 347-357, January.
    • Handle: RePEc:pal:assmgt:v:7:y:2007:i:5:d:10.1057_palgrave.jam.2250040
    DOI: 10.1057/palgrave.jam.2250040
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    Citations

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    Cited by:

    1. Hayette Gatfaoui, 2010. "Deviation from normality and Sharpe ratio behavior: a brief simulation study," Post-Print hal-00568613, HAL.
    2. Schuster, Martin & Auer, Benjamin R., 2012. "A note on empirical Sharpe ratio dynamics," Economics Letters, Elsevier, vol. 116(1), pages 124-128.
    3. U D Kumar & A B Roy & H Saranga & K Singal, 2010. "Analysis of hedge fund strategies using slack-based DEA models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(12), pages 1746-1760, December.
    4. PANAGIOTIS Anastasiadis & EFTHIMIOS Katsaros & ANASTASIOS-TAXIARCHIS KOUTSIOUKIS, 2020. "Performance-Risk Nexus Of Global Low-Rated Etfs During The Qe-Tapering Period," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 15(1), pages 194-211, April.
    5. Huck, Nicolas, 2019. "Large data sets and machine learning: Applications to statistical arbitrage," European Journal of Operational Research, Elsevier, vol. 278(1), pages 330-342.
    6. Syed Kumail Abbas Rizvi & Nawazish Mirza & Bushra Naqvi & Birjees Rahat, 2020. "Covid-19 and asset management in EU: a preliminary assessment of performance and investment styles," Journal of Asset Management, Palgrave Macmillan, vol. 21(4), pages 281-291, July.
    7. Ronald Jean Degen, 2011. "Designing Modern Equity Portfolios," Working Papers 74, globADVANTAGE, Polytechnic Institute of Leiria.
    8. Guillermo Badía & Vicente Pina & Lourdes Torres, 2019. "Financial Performance of Government Bond Portfolios Based on Environmental, Social and Governance Criteria," Sustainability, MDPI, vol. 11(9), pages 1-13, April.
    9. Korn, Olaf & Möller, Philipp M. & Schwehm, Christian, 2019. "Drawdown measures: Are they all the same?," CFR Working Papers 19-04, University of Cologne, Centre for Financial Research (CFR).
    10. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2018. "Asset allocation: new evidence through network approaches," Papers 1810.09825, arXiv.org.
    11. Grose, Chris & Dasilas, Apostolos & Alexakis, Christos, 2014. "Performance persistence in fixed interest funds: With an eye on the post-debt crisis period," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 155-182.
    12. Angelini, Pierpaolo & Maturo, Fabrizio, 2022. "The price of risk based on multilinear measures," International Review of Economics & Finance, Elsevier, vol. 81(C), pages 39-57.
    13. Sun, Bowen & Li, Huajiao & An, Pengli & Wang, Ze, 2020. "Dynamic energy stock selection based on shareholders’ coholding network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    14. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2021. "Asset allocation: new evidence through network approaches," Annals of Operations Research, Springer, vol. 299(1), pages 61-80, April.
    15. Gaydon, D.S. & Meinke, H. & Rodriguez, D. & McGrath, D.J., 2012. "Comparing water options for irrigation farmers using Modern Portfolio Theory," Agricultural Water Management, Elsevier, vol. 115(C), pages 1-9.
    16. Sebastian Krimm & Hendrik Scholz & Marco Wilkens, 2012. "The Sharpe ratio's market climate bias: Theoretical and empirical evidence from US equity mutual funds," Journal of Asset Management, Palgrave Macmillan, vol. 13(4), pages 227-242, August.
    17. Sharma, Prateek & Vipul,, 2015. "Performance of risk-based portfolios under different market conditions: Evidence from India," Research in International Business and Finance, Elsevier, vol. 34(C), pages 397-411.
    18. Anna Laskowska, 2018. "Stock Market Indices As A Measurment Tool For Profitability Of Corporate Social Responsibility Activities," Copernican Journal of Finance & Accounting, Uniwersytet Mikolaja Kopernika, vol. 7(4), pages 71-86.
    19. Syed Kumail Abbas Rizvi & Nawazish Mirza & Bushra Naqvi & Birjees Rahat, 0. "Covid-19 and asset management in EU: a preliminary assessment of performance and investment styles," Journal of Asset Management, Palgrave Macmillan, vol. 0, pages 1-11.
    20. Fei Ren & Ya-Nan Lu & Sai-Ping Li & Xiong-Fei Jiang & Li-Xin Zhong & Tian Qiu, 2017. "Dynamic Portfolio Strategy Using Clustering Approach," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-23, January.
    21. John Douglas (J.D.) Opdyke, 2007. "Comparing Sharpe ratios: So where are the p-values?," Journal of Asset Management, Palgrave Macmillan, vol. 8(5), pages 308-336, December.
    22. Lu, Jin-Ray & Li, Xiu-Yan, 2021. "Identifying the fair value of Sharpe ratio by an option valuation approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 63-70.

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