(This abstract was borrowed from another version of this item.)"> (This abstract was borrowed from another version of this item.)">
[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/wop/iasawp/ir98041.html
   My bibliography  Save this paper

Extending the MAD Portfolio Optimization Model to Incorporate Downside Risk Aversion

Author

Listed:
  • W. Michalowski
  • W. Ogryczak
Abstract
A mathematical model of portfolio optimization is usually represented as a bicriteria optimization problem where a reasonable tradeoff between expected rate of return and risk is sought. In a classical Markowitz model, the risk is measured by a variance, thus resulting in a quadratic programming model. As an alternative, the MAD model was developed by Konno and Yamazaki, where risk is measured by (mean) absolute deviation instead of a variance. The MAD model is computationally attractive, since it is easily transformed into a linear programming problem. An extension to the MAD model proposed in this paper allows us to measure risk using downside deviations, with the ability to penalize larger downside deviations. Hence, it provides for better modeling of risk averse preferences. The resulting m‐MAD model generates efficient solutions with respect to second degree stochastic dominance, while at the same time preserving the simplicity and linearity of the original MAD model. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 185–200, 2001
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • W. Michalowski & W. Ogryczak, 1998. "Extending the MAD Portfolio Optimization Model to Incorporate Downside Risk Aversion," Working Papers ir98041, International Institute for Applied Systems Analysis.
    • Handle: RePEc:wop:iasawp:ir98041
    as

    Download full text from publisher

    File URL: http://www.iiasa.ac.at/Publications/Documents/IR-98-041.pdf
    Download Restriction: no
    File URL: http://www.iiasa.ac.at/Publications/Documents/IR-98-041.ps
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Fishburn, Peter C, 1977. "Mean-Risk Analysis with Risk Associated with Below-Target Returns," American Economic Review, American Economic Association, vol. 67(2), pages 116-126, March.
    2. A. Charnes & W. W. Cooper & R. O. Ferguson, 1955. "Optimal Estimation of Executive Compensation by Linear Programming," Management Science, INFORMS, vol. 1(2), pages 138-151, January.
    3. William F. Sharpe, 1971. "Mean-Absolute-Deviation Characteristic Lines for Securities and Portfolios," Management Science, INFORMS, vol. 18(2), pages 1-13, October.
    4. G. Hanoch & H. Levy, 1969. "The Efficiency Analysis of Choices Involving Risk," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 36(3), pages 335-346.
    5. Sharpe, William F., 1971. "A Linear Programming Approximation for the General Portfolio Analysis Problem," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 6(5), pages 1263-1275, December.
    6. Ogryczak, Wlodzimierz & Ruszczynski, Andrzej, 1999. "From stochastic dominance to mean-risk models: Semideviations as risk measures," European Journal of Operational Research, Elsevier, vol. 116(1), pages 33-50, July.
    7. Peter C. Fishburn, 1980. "Stochastic Dominance and Moments of Distributions," Mathematics of Operations Research, INFORMS, vol. 5(1), pages 94-100, February.
    8. Hiroshi Konno & Hiroaki Yamazaki, 1991. "Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market," Management Science, INFORMS, vol. 37(5), pages 519-531, May.
    9. Haim Levy, 1992. "Stochastic Dominance and Expected Utility: Survey and Analysis," Management Science, INFORMS, vol. 38(4), pages 555-593, April.
    10. Rothschild, Michael & Stiglitz, Joseph E., 1970. "Increasing risk: I. A definition," Journal of Economic Theory, Elsevier, vol. 2(3), pages 225-243, September.
    11. Grootveld, Henk & Hallerbach, Winfried, 1999. "Variance vs downside risk: Is there really that much difference?," European Journal of Operational Research, Elsevier, vol. 114(2), pages 304-319, April.
    12. W. Ogryczak & A. Ruszczynski, 1997. "On Stochastic Dominance and Mean-Semideviation Models," Working Papers ir97043, International Institute for Applied Systems Analysis.
    13. Yusif Simaan, 1997. "Estimation Risk in Portfolio Selection: The Mean Variance Model Versus the Mean Absolute Deviation Model," Management Science, INFORMS, vol. 43(10), pages 1437-1446, October.
    14. Kroll, Yoram & Levy, Haim & Markowitz, Harry M, 1984. "Mean-Variance versus Direct Utility Maximization," Journal of Finance, American Finance Association, vol. 39(1), pages 47-61, March.
    15. Michael Rothschild & Joseph E. Stiglitz, 1969. "Increasing Risk: A Definition and Its Economic Consequences," Cowles Foundation Discussion Papers 275, Cowles Foundation for Research in Economics, Yale University.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Diana Barro & Elio Canestrelli, 2014. "Downside risk in multiperiod tracking error models," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(2), pages 263-283, June.
    2. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2022. "Robust portfolio selection problems: a comprehensive review," Operational Research, Springer, vol. 22(4), pages 3203-3264, September.
    3. James DiLellio, 2015. "A Kalman filter control technique in mean-variance portfolio management," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(2), pages 235-261, April.
    4. Diana Barro & Elio Canestrelli & Fabio Lanza, 2014. "Volatility vs. downside risk: optimally protecting against drawdowns and maintaining portfolio performance," Working Papers 2014:18, Department of Economics, University of Venice "Ca' Foscari".
    5. Ralph Steuer & Yue Qi & Markus Hirschberger, 2007. "Suitable-portfolio investors, nondominated frontier sensitivity, and the effect of multiple objectives on standard portfolio selection," Annals of Operations Research, Springer, vol. 152(1), pages 297-317, July.
    6. Diana Barro & Elio Canestrelli, 2012. "Dynamic tracking error with shortfall control using stochastic programming," Working Papers 2012_18, Department of Economics, University of Venice "Ca' Foscari", revised 2012.
    7. Panagiotis Xidonas & George Mavrotas & John Psarras, 2010. "Equity portfolio construction and selection using multiobjective mathematical programming," Journal of Global Optimization, Springer, vol. 47(2), pages 185-209, June.
    8. Mansini, Renata & Ogryczak, Wlodzimierz & Speranza, M. Grazia, 2014. "Twenty years of linear programming based portfolio optimization," European Journal of Operational Research, Elsevier, vol. 234(2), pages 518-535.
    9. Diana Barro & Elio Canestrelli & Giorgio Consigli, 2019. "Volatility versus downside risk: performance protection in dynamic portfolio strategies," Computational Management Science, Springer, vol. 16(3), pages 433-479, July.
    10. Shrey Jain & Siddhartha P. Chakrabarty, 2020. "Does Marginal VaR Lead to Improved Performance of Managed Portfolios: A Study of S&P BSE 100 and S&P BSE 200," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(2), pages 291-323, June.
    11. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2021. "Robust Portfolio Selection Problems: A Comprehensive Review," Papers 2103.13806, arXiv.org, revised Jan 2022.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Schuhmacher, Frank & Auer, Benjamin R., 2014. "Sufficient conditions under which SSD- and MR-efficient sets are identical," European Journal of Operational Research, Elsevier, vol. 239(3), pages 756-763.
    2. Mansini, Renata & Ogryczak, Wlodzimierz & Speranza, M. Grazia, 2014. "Twenty years of linear programming based portfolio optimization," European Journal of Operational Research, Elsevier, vol. 234(2), pages 518-535.
    3. Ogryczak, Wlodzimierz & Ruszczynski, Andrzej, 1999. "From stochastic dominance to mean-risk models: Semideviations as risk measures," European Journal of Operational Research, Elsevier, vol. 116(1), pages 33-50, July.
    4. Sergio Ortobelli Lozza, 2001. "The classification of parametric choices under uncertainty: analysis of the portfolio choice problem," Theory and Decision, Springer, vol. 51(2), pages 297-328, December.
    5. Bai, Zhidong & Liu, Huixia & Wong, Wing-Keung, 2016. "Making Markowitz's Portfolio Optimization Theory Practically Useful," MPRA Paper 74360, University Library of Munich, Germany.
    6. W. Ogryczak & A. Ruszczynski, 1997. "On Stochastic Dominance and Mean-Semideviation Models," Working Papers ir97043, International Institute for Applied Systems Analysis.
    7. Jun-ya Gotoh & Hiroshi Konno, 2000. "Third Degree Stochastic Dominance and Mean-Risk Analysis," Management Science, INFORMS, vol. 46(2), pages 289-301, February.
    8. Dentcheva, Darinka & Ruszczynski, Andrzej, 2006. "Portfolio optimization with stochastic dominance constraints," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 433-451, February.
    9. Levy, Moshe, 2009. "Almost Stochastic Dominance and stocks for the long run," European Journal of Operational Research, Elsevier, vol. 194(1), pages 250-257, April.
    10. Fong, Wai Mun, 2016. "Stochastic dominance and the omega ratio," Finance Research Letters, Elsevier, vol. 17(C), pages 7-9.
    11. Post, G.T., 2001. "Testing for Stochastic Dominance with Diversification Possibilities," ERIM Report Series Research in Management ERS-2001-38-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    12. Nowak, Maciej, 2004. "Preference and veto thresholds in multicriteria analysis based on stochastic dominance," European Journal of Operational Research, Elsevier, vol. 158(2), pages 339-350, October.
    13. Alessandra Carleo & Francesco Cesarone & Andrea Gheno & Jacopo Maria Ricci, 2017. "Approximating exact expected utility via portfolio efficient frontiers," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 40(1), pages 115-143, November.
    14. Janne Gustafsson & Ahti Salo, 2005. "Contingent Portfolio Programming for the Management of Risky Projects," Operations Research, INFORMS, vol. 53(6), pages 946-956, December.
    15. Caporin, Massimiliano & Costola, Michele & Jannin, Gregory & Maillet, Bertrand, 2018. "“On the (Ab)use of Omega?”," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 11-33.
    16. Wong, Wing-Keung, 2007. "Stochastic dominance and mean-variance measures of profit and loss for business planning and investment," European Journal of Operational Research, Elsevier, vol. 182(2), pages 829-843, October.
    17. Francesco Cesarone & Raffaello Cesetti & Giuseppe Orlando & Manuel Luis Martino & Jacopo Maria Ricci, 2022. "Comparing SSD-Efficient Portfolios with a Skewed Reference Distribution," Mathematics, MDPI, vol. 11(1), pages 1-20, December.
    18. Kaplanski, Guy & Kroll, Yoram, 2002. "VaR Risk Measures versus Traditional Risk Measures: an Analysis and Survey," MPRA Paper 80070, University Library of Munich, Germany.
    19. Amita Sharma & Aparna Mehra, 2017. "Financial analysis based sectoral portfolio optimization under second order stochastic dominance," Annals of Operations Research, Springer, vol. 256(1), pages 171-197, September.
    20. Cillo, Alessandra & Delquié, Philippe, 2014. "Mean-risk analysis with enhanced behavioral content," European Journal of Operational Research, Elsevier, vol. 239(3), pages 764-775.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wop:iasawp:ir98041. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thomas Krichel (email available below). General contact details of provider: https://edirc.repec.org/data/iiasaat.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.