IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v177y2010i1p63-9010.1007-s10479-009-0592-6.html
   My bibliography  Save this article

Portfolio optimization for wealth-dependent risk preferences

Author

Listed:
  • Luis Rios
  • Nikolaos Sahinidis

Abstract

Empirical and theoretical studies of preference structures of investors have long shown that personal and corporate utility is typically multimodal, implying that the same investor can be risk-averse at certain levels of wealth while risk-seeking at others. In this paper, we consider the problem of optimizing the portfolio of an investor with an indefinite quadratic utility function. The convex and concave segments of this utility reflect the investor’s attitude towards risk, which changes based on deviations from a fixed goal. Uncertainty is modeled via a finite set of scenarios for the returns of securities. A global optimization approach is developed to solve the proposed nonconvex optimization problem. We present computational results which investigate the effect of short sales and demonstrate that the proposed approach systematically produces portfolios with higher values of skewness than the classical expectation-variance approach. Copyright Springer Science+Business Media, LLC 2010

Suggested Citation

  • Luis Rios & Nikolaos Sahinidis, 2010. "Portfolio optimization for wealth-dependent risk preferences," Annals of Operations Research, Springer, vol. 177(1), pages 63-90, June.
    • Handle: RePEc:spr:annopr:v:177:y:2010:i:1:p:63-90:10.1007/s10479-009-0592-6
    DOI: 10.1007/s10479-009-0592-6
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-009-0592-6
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10479-009-0592-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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. R. T. Rockafellar & Roger J.-B. Wets, 1991. "Scenarios and Policy Aggregation in Optimization Under Uncertainty," Mathematics of Operations Research, INFORMS, vol. 16(1), pages 119-147, February.
    3. Mulvey, John M. & Rosenbaum, Daniel P. & Shetty, Bala, 1997. "Strategic financial risk management and operations research," European Journal of Operational Research, Elsevier, vol. 97(1), pages 1-16, February.
    4. Joost M. E. Pennings & Ale Smidts, 2003. "The Shape of Utility Functions and Organizational Behavior," Management Science, INFORMS, vol. 49(9), pages 1251-1263, September.
    5. Markowitz, Harry M & Perold, Andre F, 1981. "Portfolio Analysis with Factors and Scenarios," Journal of Finance, American Finance Association, vol. 36(4), pages 871-877, September.
    6. Ron S. Dembo & Alan J. King, 1992. "Tracking models and the optimal regret distribution in asset allocation," Applied Stochastic Models and Data Analysis, John Wiley & Sons, vol. 8(3), pages 151-157, September.
    7. 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.
    8. Milton Friedman & L. J. Savage, 1948. "The Utility Analysis of Choices Involving Risk," Journal of Political Economy, University of Chicago Press, vol. 56, pages 279-279.
    9. Kane, Alex, 1982. "Skewness Preference and Portfolio Choice," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 17(1), pages 15-25, March.
    10. 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.
    11. Holthausen, Duncan M, 1981. "A Risk-Return Model with Risk and Return Measured as Deviations from a Target Return," American Economic Review, American Economic Association, vol. 71(1), pages 182-188, March.
    12. John M. Mulvey, 1996. "Generating Scenarios for the Towers Perrin Investment System," Interfaces, INFORMS, vol. 26(2), pages 1-15, April.
    13. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    14. John M. Mulvey, 1994. "An Asset-Liability Investment System," Interfaces, INFORMS, vol. 24(3), pages 22-33, June.
    15. Friedman, Daniel, 1989. "The S-Shaped Value Function as a Constrained Optimum," American Economic Review, American Economic Association, vol. 79(5), pages 1243-1248, December.
    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. Boukouvala, Fani & Misener, Ruth & Floudas, Christodoulos A., 2016. "Global optimization advances in Mixed-Integer Nonlinear Programming, MINLP, and Constrained Derivative-Free Optimization, CDFO," European Journal of Operational Research, Elsevier, vol. 252(3), pages 701-727.
    2. Cooper, W.W. & Kingyens, Angela T. & Paradi, Joseph C., 2014. "Two-stage financial risk tolerance assessment using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 233(1), pages 273-280.

    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. 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.
    2. 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.
    3. Fulga, Cristinca, 2016. "Portfolio optimization under loss aversion," European Journal of Operational Research, Elsevier, vol. 251(1), pages 310-322.
    4. Wojtek Michalowski & Włodzimierz Ogryczak, 2001. "Extending the MAD portfolio optimization model to incorporate downside risk aversion," Naval Research Logistics (NRL), John Wiley & Sons, vol. 48(3), pages 185-200, April.
    5. Karma, Otto & Sander, Priit, 2006. "The impact of financial leverage on risk of equity measured by loss-oriented risk measures: An option pricing approach," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1340-1356, December.
    6. Wakker, Peter P. & Zank, Horst, 2002. "A simple preference foundation of cumulative prospect theory with power utility," European Economic Review, Elsevier, vol. 46(7), pages 1253-1271, July.
    7. Capitani, Daniel Henrique Dario & Mattos, Fabio, 2012. "Risk measurement in commodities markets: How much price risk do agricultural producers really face?," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124761, Agricultural and Applied Economics Association.
    8. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
    9. Robert Jarrow & Feng Zhao, 2006. "Downside Loss Aversion and Portfolio Management," Management Science, INFORMS, vol. 52(4), pages 558-566, April.
    10. 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.
    11. Cochran, Mark J., 1986. "Stochastic Dominance: The State Of The Art In Agricultural Economics," Regional Research Projects > 1986: S-180 Annual Meeting, March 23-26, 1986, Tampa, Florida 271995, Regional Research Projects > S-180: An Economic Analysis of Risk Management Strategies for Agricultural Production Firms.
    12. Anthonisz, Sean A., 2012. "Asset pricing with partial-moments," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2122-2135.
    13. 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.
    14. León, Ángel & Moreno, Manuel, 2015. "Lower Partial Moments under Gram Charlier Distribution: Performance Measures and Efficient Frontiers," QM&ET Working Papers 15-3, University of Alicante, D. Quantitative Methods and Economic Theory.
    15. ManMohan S. Sodhi, 2005. "LP Modeling for Asset-Liability Management: A Survey of Choices and Simplifications," Operations Research, INFORMS, vol. 53(2), pages 181-196, April.
    16. Mark Schneider & Robert Day, 2018. "Target-Adjusted Utility Functions and Expected-Utility Paradoxes," Management Science, INFORMS, vol. 64(1), pages 271-287, January.
    17. Kang, Taehoon & Wade Brorsen, B. & Adam, Brian D., 1996. "A new efficiency criterion: The mean-separated target deviations risk model," Journal of Economics and Business, Elsevier, vol. 48(1), pages 47-66, February.
    18. Dipankar Mondal & N. Selvaraju, 2022. "Convexity, two-fund separation and asset ranking in a mean-LPM portfolio selection framework," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(1), pages 225-248, March.
    19. Brogan, Anita J. & Stidham Jr., Shaler, 2008. "Non-separation in the mean-lower-partial-moment portfolio optimization problem," European Journal of Operational Research, Elsevier, vol. 184(2), pages 701-710, January.
    20. Tronstad, Russell & McNeill, Thomas J., 1987. "An Alternative Measure of Price Risk on Aggregate Sow Farrowings, 1973-86," 1987 Annual Meeting, August 2-5, East Lansing, Michigan 269961, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

    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:spr:annopr:v:177:y:2010:i:1:p:63-90:10.1007/s10479-009-0592-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.