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A Robust Sharpe Ratio

Author

Listed:
  • Mahesh K.C

    (Institute of Management, Nirma University)

  • Arnab Kumar Laha

    (Indian Institute of Management Ahmedabad)

Abstract

Sharpe ratio is one of the widely used measures in the financial literature to compare two or more investment strategies. Since it is a ratio of the excess expected return of a portfolio to its standard deviation of returns, it is not robust against the presence of outliers. In this paper we propose a modification of the Sharpe ratio which is based on robust measures of location and scale. We investigate the properties of this proposed ratio under six alternative return distributions. It is seen that the modified Sharpe ratio performs better than the original Sharpe ratio in the presence of outliers. A real life stock market return data set is analyzed and the comparative performances of the two ratios are studied. The results indicate that modified Sharpe ratio may be a better measure for comparing different investment strategies. When downside risk is the only concern of the investors a modification of the Sharpe ratio known as Sortino ratio is often used. It is shown that the Sortino ratio is not robust and we propose a modified version of the same which is robust.

Suggested Citation

  • Mahesh K.C & Arnab Kumar Laha, 2021. "A Robust Sharpe Ratio," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 444-465, November.
  • Handle: RePEc:spr:sankhb:v:83:y:2021:i:2:d:10.1007_s13571-019-00204-y
    DOI: 10.1007/s13571-019-00204-y
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    References listed on IDEAS

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    1. John Knight & Stephen Satchell, 2005. "A Re-Examination of Sharpe's Ratio for Log-Normal Prices," Applied Mathematical Finance, Taylor & Francis Journals, vol. 12(1), pages 87-100.
    2. Ledoit, Oliver & Wolf, Michael, 2008. "Robust performance hypothesis testing with the Sharpe ratio," Journal of Empirical Finance, Elsevier, vol. 15(5), pages 850-859, December.
    3. Jobson, J D & Korkie, Bob M, 1981. "Performance Hypothesis Testing with the Sharpe and Treynor Measures," Journal of Finance, American Finance Association, vol. 36(4), pages 889-908, September.
    4. 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.
    5. Nielsen, Lars Tyge & Vassalou, Maria, 2004. "Sharpe Ratios and Alphas in Continuous Time," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(1), pages 103-114, March.
    6. Falk, Michael, 1997. "Asymptotic independence of median and MAD," Statistics & Probability Letters, Elsevier, vol. 34(4), pages 341-345, June.
    7. André F. Perold, 2004. "The Capital Asset Pricing Model," Journal of Economic Perspectives, American Economic Association, vol. 18(3), pages 3-24, Summer.
    8. Bao, Yong & Ullah, Aman, 2006. "Moments of the estimated Sharpe ratio when the observations are not IID," Finance Research Letters, Elsevier, vol. 3(1), pages 49-56, March.
    9. Miller, Robert E. & Gehr, Adam K., 1978. "Sample Size Bias and Sharpe's Performance Measure: A Note," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 13(5), pages 943-946, December.
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