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A Note on Trader Sharpe Ratios

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  • John M Coates
  • Lionel Page

Abstract

Traders in the financial world are assessed by the amount of money they make and, increasingly, by the amount of money they make per unit of risk taken, a measure known as the Sharpe Ratio. Little is known about the average Sharpe Ratio among traders, but the Efficient Market Hypothesis suggests that traders, like asset managers, should not outperform the broad market. Here we report the findings of a study conducted in the City of London which shows that a population of experienced traders attain Sharpe Ratios significantly higher than the broad market. To explain this anomaly we examine a surrogate marker of prenatal androgen exposure, the second-to-fourth finger length ratio (2D∶4D), which has previously been identified as predicting a trader's long term profitability. We find that it predicts the amount of risk taken by traders but not their Sharpe Ratios. We do, however, find that the traders' Sharpe Ratios increase markedly with the number of years they have traded, a result suggesting that learning plays a role in increasing the returns of traders. Our findings present anomalous data for the Efficient Markets Hypothesis.

Suggested Citation

  • John M Coates & Lionel Page, 2009. "A Note on Trader Sharpe Ratios," PLOS ONE, Public Library of Science, vol. 4(11), pages 1-5, November.
    • Handle: RePEc:plo:pone00:0008036
    DOI: 10.1371/journal.pone.0008036
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    References listed on IDEAS

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    Cited by:

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    2. Yi-Fang Liu & Jørgen Vitting Andersen & Philippe de Peretti, 2016. "Onset of financial instability studied via agent-based models," Post-Print hal-01397400, HAL.
    3. Bruno Gav{s}perov & Zvonko Kostanjv{c}ar, 2022. "Deep Reinforcement Learning for Market Making Under a Hawkes Process-Based Limit Order Book Model," Papers 2207.09951, arXiv.org.
    4. Meier, Philippe & Flepp, Raphael & Ruedisser, Maximilian & Franck, Egon, 2020. "Separating psychological momentum from strategic momentum: Evidence from men’s professional tennis," Journal of Economic Psychology, Elsevier, vol. 78(C).
    5. Zhixin Xie & Lionel Page & Ben Hardy, 2016. "Investigating gender differences under time pressure in financial risk taking," QuBE Working Papers 045, QUT Business School.
    6. Da Silva, Sergio & Baldo, Dinora & Matsushita, Raul, 2011. "Biological correlates of the Allais paradox - updated," MPRA Paper 32747, University Library of Munich, Germany.
    7. Werner Bönte & Vivien D. Procher & Diemo Urbig, 2016. "Biology and Selection into Entrepreneurship—The Relevance of Prenatal Testosterone Exposure," Entrepreneurship Theory and Practice, , vol. 40(5), pages 1121-1148, September.
    8. Bose, Subir & Ladley, Daniel & Li, Xin, 2020. "The role of hormones in financial markets," International Review of Financial Analysis, Elsevier, vol. 67(C).
    9. Xing Gao & Daniel Ladley, 2022. "Noise trading and market stability," The European Journal of Finance, Taylor & Francis Journals, vol. 28(13-15), pages 1283-1301, October.
    10. Erik Bijleveld & Joost Baalbergen, 2017. "Prenatal exposure to testosterone (2D:4D) and social hierarchy together predict voice behavior in bankers," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-13, June.
    11. Ladley, Daniel & Lensberg, Terje & Palczewski, Jan & Schenk-Hoppé, Klaus Reiner, 2015. "Fragmentation and stability of markets," Journal of Economic Behavior & Organization, Elsevier, vol. 119(C), pages 466-481.
    12. Yi-Fang Liu & Jørgen Vitting Andersen & Maxime Frolov & Philippe de Peretti, 2016. "Synchronization in human decision making," Post-Print halshs-01317407, HAL.
    13. Nicos Nicolaou & Pankaj C. Patel & Marcus T. Wolfe, 2018. "Testosterone and Tendency to Engage in Self-Employment," Management Science, INFORMS, vol. 64(4), pages 1825-1841, April.
    14. Pablo Brañas-Garza & Aldo Rustichini, 2011. "Organizing Effects of Testosterone and Economic Behavior: Not Just Risk Taking," PLOS ONE, Public Library of Science, vol. 6(12), pages 1-8, December.
    15. Yi-Fang Liu & Jørgen Vitting Andersen & Maxime Frolov & Philippe de Peretti, 2016. "Synchronization in human decision making," Documents de travail du Centre d'Economie de la Sorbonne 16035, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    16. Andreas C. Drichoutis & Rodolfo M. Nayga, 2015. "Do risk and time preferences have biological roots?," Southern Economic Journal, John Wiley & Sons, vol. 82(1), pages 235-256, July.
    17. Friedl, Andreas & Neyse, Levent & Schmidt, Ulrich, 2018. "Payment scheme changes and effort Adjustment: The role of 2D:4D digit ratio," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 72(C), pages 86-94.
    18. Yi-Fang Liu & Jørgen Vitting Andersen & Maxime Frolov & Philippe de Peretti, 2016. "Synchronization in human decision making," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01317407, HAL.

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