IDEAS home Printed from https://ideas.repec.org/a/taf/quantf/v14y2014i4p657-671.html

Optimal portfolios under worst-case scenarios

Author

Listed:
  • Carole Bernard
  • Jit Seng Chen
  • Steven Vanduffel

Abstract

In standard portfolio theories such as Mean-Variance optimization, expected utility theory, rank dependent utility heory, Yaari's dual theory and cumulative prospect theory, the worst outcomes for optimal strategies occur when the market declines (e.g. during crises), which is at odds with the needs of many investors. Hence, we depart from the traditional settings and study optimal strategies for investors who impose additional constraints on their final wealth in the states corresponding to a stressed financial market. We provide a framework that maintains the stylized features of the SP/A theory while dealing with the goal of security in a more flexible way. Preferences become state-dependent , and we assess the impact of these preferences on trading decisions. We construct optimal strategies explicitly and show how they outperform traditional diversified strategies under worst-case scenarios.

Suggested Citation

  • Carole Bernard & Jit Seng Chen & Steven Vanduffel, 2014. "Optimal portfolios under worst-case scenarios," Quantitative Finance, Taylor & Francis Journals, vol. 14(4), pages 657-671, April.
    • Handle: RePEc:taf:quantf:v:14:y:2014:i:4:p:657-671
    DOI: 10.1080/14697688.2013.836282
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/14697688.2013.836282
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/14697688.2013.836282?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 look for a different version below or

    for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Acharya, Viral V., 2009. "A theory of systemic risk and design of prudential bank regulation," Journal of Financial Stability, Elsevier, vol. 5(3), pages 224-255, September.
    2. Yaari, Menahem E, 1987. "The Dual Theory of Choice under Risk," Econometrica, Econometric Society, vol. 55(1), pages 95-115, January.
    3. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    4. Philip H. Dybvig, 1988. "Inefficient Dynamic Portfolio Strategies or How to Throw Away a Million Dollars in the Stock Market," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 67-88.
    5. Peter Tankov, 2010. "Improved Frechet bounds and model-free pricing of multi-asset options," Papers 1004.4153, arXiv.org, revised Mar 2011.
    6. Long, John Jr., 1990. "The numeraire portfolio," Journal of Financial Economics, Elsevier, vol. 26(1), pages 29-69, July.
    7. Steven Vanduffel & Andrew Chernih & Matheusz Maj & Wim Schoutens, 2009. "A Note on the Suboptimality of Path-Dependent Pay-Offs in Levy Markets," Applied Mathematical Finance, Taylor & Francis Journals, vol. 16(4), pages 315-330.
    8. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    9. Carole Bernard & Mateusz Maj & Steven Vanduffel, 2011. "Improving the Design of Financial Products in a Multidimensional Black-Scholes Market," North American Actuarial Journal, Taylor & Francis Journals, vol. 15(1), pages 77-96.
    10. Beare, Brendan K., 2011. "Measure preserving derivatives and the pricing kernel puzzle," Journal of Mathematical Economics, Elsevier, vol. 47(6), pages 689-697.
    11. Ibragimov, Rustam & Jaffee, Dwight & Walden, Johan, 2011. "Diversification disasters," Journal of Financial Economics, Elsevier, vol. 99(2), pages 333-348, February.
    12. Milton Friedman & L. J. Savage, 1948. "The Utility Analysis of Choices Involving Risk," Journal of Political Economy, University of Chicago Press, vol. 56(4), pages 279-279.
    13. Shefrin, Hersh & Statman, Meir, 2000. "Behavioral Portfolio Theory," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(2), pages 127-151, June.
    14. Valery Polkovnichenko, 2005. "Household Portfolio Diversification: A Case for Rank-Dependent Preferences," The Review of Financial Studies, Society for Financial Studies, vol. 18(4), pages 1467-1502.
    15. Daniel G. Goldstein & Eric J. Johnson & William F. Sharpe, 2008. "Choosing Outcomes versus Choosing Products: Consumer-Focused Retirement Investment Advice," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 35(3), pages 440-456, August.
    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. Bernard, Carole & Vanduffel, Steven, 2015. "A new approach to assessing model risk in high dimensions," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 166-178.
    2. Bernard, Carole & Vanduffel, Steven & Ye, Jiang, 2019. "A new efficiency test for ranking investments: Application to hedge fund performance," Economics Letters, Elsevier, vol. 181(C), pages 203-207.
    3. Bernard, Carole & Chen, Jit Seng & Vanduffel, Steven, 2015. "Rationalizing investors’ choices," Journal of Mathematical Economics, Elsevier, vol. 59(C), pages 10-23.
    4. Bilgi Yilmaz, 2025. "Optimal Portfolios for Large Investors in Housing Markets Under Stress Scenarios: A Worst-Case Approach," Computational Economics, Springer;Society for Computational Economics, vol. 65(5), pages 2853-2871, May.

    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. L. Rüschendorf & Steven Vanduffel, 2020. "On the construction of optimal payoffs," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 43(1), pages 129-153, June.
    2. Bernard, Carole & Chen, Jit Seng & Vanduffel, Steven, 2015. "Rationalizing investors’ choices," Journal of Mathematical Economics, Elsevier, vol. 59(C), pages 10-23.
    3. Stephen G Dimmock & Roy Kouwenberg & Olivia S Mitchell & Kim Peijnenburg, 2021. "Household Portfolio Underdiversification and Probability Weighting: Evidence from the Field," The Review of Financial Studies, Society for Financial Studies, vol. 34(9), pages 4524-4563.
    4. Montone, Maurizio, 2023. "Beta, value, and growth: Do dichotomous risk-preferences explain stock returns?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    5. Levy, Haim & Wiener, Zvi, 2013. "Prospect theory and utility theory: Temporary versus permanent attitude toward risk," Journal of Economics and Business, Elsevier, vol. 68(C), pages 1-23.
    6. Fajardo, José & Corcuera, José Manuel & Menouken Pamen, Olivier, 2016. "On the optimal investment," MPRA Paper 71901, University Library of Munich, Germany.
    7. Jakusch, Sven Thorsten & Meyer, Steffen & Hackethal, Andreas, 2019. "Taming models of prospect theory in the wild? Estimation of Vlcek and Hens (2011)," SAFE Working Paper Series 146, Leibniz Institute for Financial Research SAFE, revised 2019.
    8. Kuo-Hwa Chang & Michael Nayat Young, 2019. "Portfolios Optimizations of Behavioral Stocks with Perception Probability Weightings," Annals of Economics and Finance, Society for AEF, vol. 20(2), pages 817-845, November.
    9. 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.
    10. Hsin, Chin-Wen & Peng, Shu-Cing, 2023. "Investor propensity to speculate and price delay in emerging markets," International Review of Financial Analysis, Elsevier, vol. 86(C).
    11. Qizhu Liang & Jie Xiong, 2017. "Stochastic maximum principle under probability distortion," Papers 1710.11432, arXiv.org, revised Aug 2018.
    12. Pavlo Blavatskyy, 2024. "A puzzle of roulette gambling," Journal of Risk and Uncertainty, Springer, vol. 69(2), pages 219-234, October.
    13. Trabelsi, Mohamed Ali, 2006. "Les nouveaux modèles de décision dans le risque et l’incertain : quel apport ? [The new models of decision under risk or uncertainty : What approach?]," MPRA Paper 25442, University Library of Munich, Germany.
    14. Valeri Zakamouline & Steen Koekebakker, 2009. "A Generalisation of the Mean†Variance Analysis," European Financial Management, European Financial Management Association, vol. 15(5), pages 934-970, November.
    15. Pavlo Blavatskyy, 2018. "A second-generation disappointment aversion theory of decision making under risk," Theory and Decision, Springer, vol. 84(1), pages 29-60, January.
    16. Bi, Junna & Jin, Hanqing & Meng, Qingbin, 2018. "Behavioral mean-variance portfolio selection," European Journal of Operational Research, Elsevier, vol. 271(2), pages 644-663.
    17. Raquel M. Gaspar & Paulo M. Silva, 2019. "Investors’ Perspective on Portfolio InsuranceExpected Utility vs Prospect Theories," Working Papers REM 2019/92, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    18. Sudeep Bhatia & Graham Loomes & Daniel Read, 2021. "Establishing the laws of preferential choice behavior," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 16(6), pages 1324-1369, November.
    19. Hanqing Jin & Xun Yu Zhou, 2008. "Behavioral Portfolio Selection In Continuous Time," Mathematical Finance, Wiley Blackwell, vol. 18(3), pages 385-426, July.
    20. Harris, Richard D. F. & Mazibas, Murat, 2022. "Portfolio optimization with behavioural preferences and investor memory," European Journal of Operational Research, Elsevier, vol. 296(1), pages 368-387.

    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:taf:quantf:v:14:y:2014:i:4:p:657-671. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RQUF20 .

    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.