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Effective return, risk aversion and drawdowns

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  • Dacorogna, Michel M.
  • Gençay, Ramazan
  • Müller, Ulrich A.
  • Pictet, Olivier V.

Abstract

We derive two risk-adjusted performance measures for investors with risk averse preferences. Maximizing these measures is equivalent to maximizing the expected utility of an investor. The first measure, Xeff, is derived assuming a constant risk aversion while the second measure, Reff, is based on a stronger risk aversion to clustering of losses than of gains. The clustering of returns is captured through a multi-horizon framework. The empirical properties of Xeff, Reff are studied within the context of real-time trading models for foreign exchange rates and their properties are compared to those of more traditional measures like the annualized return, the Sharpe Ratio and the maximum drawdown. Our measures are shown to be more robust against clustering of losses and have the ability to fully characterize the dynamic behaviour of investment strategies.

Suggested Citation

  • Dacorogna, Michel M. & Gençay, Ramazan & Müller, Ulrich A. & Pictet, Olivier V., 2001. "Effective return, risk aversion and drawdowns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 289(1), pages 229-248.
  • Handle: RePEc:eee:phsmap:v:289:y:2001:i:1:p:229-248
    DOI: 10.1016/S0378-4371(00)00462-3
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    References listed on IDEAS

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    1. Shlomo Benartzi & Richard H. Thaler, 1995. "Myopic Loss Aversion and the Equity Premium Puzzle," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(1), pages 73-92.
    2. Dacorogna, Michael M. & Muller, Ulrich A. & Nagler, Robert J. & Olsen, Richard B. & Pictet, Olivier V., 1993. "A geographical model for the daily and weekly seasonal volatility in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 12(4), pages 413-438, August.
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    Cited by:

    1. GIOT, Pierre & PETITJEAN, Mikael, 2006. "International stock return predictability: statistical evidence and economic significance," LIDAM Discussion Papers CORE 2006088, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Tavakoli Baghdadabad, Mohammad Reza, 2014. "Average drawdown risk reduction and risk tolerances," Research in Economics, Elsevier, vol. 68(3), pages 264-276.
    3. Neely, Christopher J., 2003. "Risk-adjusted, ex ante, optimal technical trading rules in equity markets," International Review of Economics & Finance, Elsevier, vol. 12(1), pages 69-87.
    4. Christopher J. Neely & Paul A. Weller, 2011. "Technical analysis in the foreign exchange market," Working Papers 2011-001, Federal Reserve Bank of St. Louis.
    5. Heidorn, Thomas & Siragusano, Tindaro, 2004. "Die Anwendbarkeit der Behavioral Finance im Devisenmarkt," Frankfurt School - Working Paper Series 52, Frankfurt School of Finance and Management.
    6. Schuhmacher, Frank & Eling, Martin, 2011. "Sufficient conditions for expected utility to imply drawdown-based performance rankings," Journal of Banking & Finance, Elsevier, vol. 35(9), pages 2311-2318, September.
    7. Ni, Yensen & Liao, Yi-Ching & Huang, Paoyu, 2015. "MA trading rules, herding behaviors, and stock market overreaction," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 253-265.
    8. Dong, Yang & Wen, Shu-hui & Hu, Xiao-bing & Li, Jiang-Cheng, 2020. "Stochastic resonance of drawdown risk in energy market prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    9. Andrew Clark, 2005. "The use of Hurst and effective return in investing," Quantitative Finance, Taylor & Francis Journals, vol. 5(1), pages 1-8.
    10. Pierre Giot & Mikael Petitjean, 2011. "On the statistical and economic performance of stock return predictive regression models: an international perspective," Quantitative Finance, Taylor & Francis Journals, vol. 11(2), pages 175-193.
    11. Xufre Casqueiro, Patricia & Rodrigues, Antonio J.L., 2006. "Neuro-dynamic trading methods," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1400-1412, December.

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