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Optimal Portfolio Selection With A Shortfall Probability Constraint: Evidence From Alternative Distribution Functions

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  • Yalcin Akcay
  • Atakan Yalcin

Abstract

We propose a new approach to optimal portfolio selection in a downside risk framework that allocates assets by maximizing expected return subject to a shortfall probability constraint, reflecting the typical desire of a risk‐averse investor to limit the maximum likely loss. Our empirical results indicate that the loss‐averse portfolio outperforms the widely used mean‐variance approach based on the cumulative cash values, geometric mean returns, and average risk‐adjusted returns. We also evaluate the relative performance of the loss‐averse portfolio with normal, symmetric thin‐tailed, symmetric fat‐tailed, and skewed fat‐tailed return distributions in terms of average return, risk, and average risk‐adjusted return.

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  • Yalcin Akcay & Atakan Yalcin, 2010. "Optimal Portfolio Selection With A Shortfall Probability Constraint: Evidence From Alternative Distribution Functions," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 33(1), pages 77-102, March.
  • Handle: RePEc:bla:jfnres:v:33:y:2010:i:1:p:77-102
    DOI: 10.1111/j.1475-6803.2009.01263.x
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    1. Hansen, Bruce E, 1994. "Autoregressive Conditional Density Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-730, August.
    2. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    3. Basak, Suleyman & Shapiro, Alexander, 2001. "Value-at-Risk-Based Risk Management: Optimal Policies and Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 14(2), pages 371-405.
    4. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2006. "The Cross‐Section of Volatility and Expected Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 259-299, February.
    5. Suleyman Basak & Alex Shapiro & Lucie Teplá, 2006. "Risk Management with Benchmarking," Management Science, INFORMS, vol. 52(4), pages 542-557, April.
    6. Eric Jondeau & Michael Rockinger, 2006. "Optimal Portfolio Allocation under Higher Moments," European Financial Management, European Financial Management Association, vol. 12(1), pages 29-55, January.
    7. Kahneman, Daniel & Knetsch, Jack L & Thaler, Richard H, 1990. "Experimental Tests of the Endowment Effect and the Coase Theorem," Journal of Political Economy, University of Chicago Press, vol. 98(6), pages 1325-1348, December.
    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. Harry Markowitz, 1952. "The Utility of Wealth," Journal of Political Economy, University of Chicago Press, vol. 60(2), pages 151-151.
    10. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
    11. Bali, Turan G. & Demirtas, K. Ozgur & Levy, Haim, 2009. "Is There an Intertemporal Relation between Downside Risk and Expected Returns?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(4), pages 883-909, August.
    12. Turan G. Bali, 2007. "An Extreme Value Approach to Estimating Interest-Rate Volatility: Pricing Implications for Interest-Rate Options," Management Science, INFORMS, vol. 53(2), pages 323-339, February.
    13. Fu, Fangjian, 2009. "Idiosyncratic risk and the cross-section of expected stock returns," Journal of Financial Economics, Elsevier, vol. 91(1), pages 24-37, January.
    14. Arditti, Fred D & Levy, Haim, 1975. "Portfolio Efficiency Analysis in Three Moments: The Multiperiod Case," Journal of Finance, American Finance Association, vol. 30(3), pages 797-809, June.
    15. Campbell R. Harvey & Akhtar Siddique, 2000. "Conditional Skewness in Asset Pricing Tests," Journal of Finance, American Finance Association, vol. 55(3), pages 1263-1295, June.
    16. Levy, Haim & Sarnat, Marshall, 1972. "Safety First — An Expected Utility Principle," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 7(3), pages 1829-1834, June.
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    Cited by:

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    2. Houda Hafsa, 2015. "CVaR in Portfolio Optimization: An Essay on the French Market," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 6(2), pages 101-111, April.
    3. Jaydip Sen & Sidra Mehtab, 2021. "Design and Analysis of Robust Deep Learning Models for Stock Price Prediction," Papers 2106.09664, arXiv.org.

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