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A Note on the E, SL Portfolio Selection Model

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  • Ang, James S.

Abstract

The purpose of this note is to present a simple computational algorithm to approximate the E, S portfolio selection model. The essential feature of the model is the utilization of the familiar linear programming framework by representing risks as a series of linear constraints. Suppose we have m states and n securities, and we assume the investor is able to specify the contingent returns for all securities in each state. Following [7], we define risk as being the downside deviation from the investor's target rate of return.

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  • Ang, James S., 1975. "A Note on the E, SL Portfolio Selection Model," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 10(5), pages 849-857, December.
    • Handle: RePEc:cup:jfinqa:v:10:y:1975:i:05:p:849-857_01
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    Cited by:

    1. Ayub, Usman & Shah, Syed Zulfiqar Ali & Abbas, Qaisar, 2015. "Robust analysis for downside risk in portfolio management for a volatile stock market," Economic Modelling, Elsevier, vol. 44(C), pages 86-96.
    2. Hanene Ben Salah & Mohamed Chaouch & Ali Gannoun & Christian Peretti & Abdelwahed Trabelsi, 2018. "Mean and median-based nonparametric estimation of returns in mean-downside risk portfolio frontier," Annals of Operations Research, Springer, vol. 262(2), pages 653-681, March.
    3. Hanene Ben Salah & Ali Gannoun & Christian De Peretti & Mathieu Ribatet & Abdelwahed Trabelsi, 2016. "A New Approach in Nonparametric Estimation of Returns in Mean-DownSide Risk Portfolio frontier," Working Papers hal-01299561, HAL.
    4. Cumova, Denisa & Nawrocki, David, 2011. "A symmetric LPM model for heuristic mean-semivariance analysis," Journal of Economics and Business, Elsevier, vol. 63(3), pages 217-236, May.
    5. Hanene Ben Salah & Mohamed Chaouch & Ali Gannoun & Christian Peretti & Abdelwahed Trabelsi, 2018. "Mean and median-based nonparametric estimation of returns in mean-downside risk portfolio frontier," Annals of Operations Research, Springer, vol. 262(2), pages 653-681, March.
    6. Cumova, Denisa & Nawrocki, David, 2014. "Portfolio optimization in an upside potential and downside risk framework," Journal of Economics and Business, Elsevier, vol. 71(C), pages 68-89.
    7. Christian de Peretti, 2015. "A New Approach in Nonparametric Estimation of Returns in Mean-Downside Risk Portfolio frontier," Post-Print hal-02095499, HAL.
    8. Leitner Johannes, 2005. "Optimal portfolios with expected loss constraints and shortfall risk optimal martingale measures," Statistics & Risk Modeling, De Gruyter, vol. 23(1/2005), pages 49-66, January.
    9. Jakobsons Edgars, 2016. "Scenario aggregation method for portfolio expectile optimization," Statistics & Risk Modeling, De Gruyter, vol. 33(1-2), pages 51-65, September.
    10. Zhangxin (Frank) Liu & Michael J. O'Neill, 2018. "Partial moment volatility indices," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(1), pages 195-215, March.

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