IDEAS home Printed from https://ideas.repec.org/a/spr/comgts/v16y2019i1d10.1007_s10287-018-0333-x.html
   My bibliography  Save this article

Portfolio choice under cumulative prospect theory: sensitivity analysis and an empirical study

Author

Listed:
  • Giorgio Consigli

    (University of Bergamo)

  • Asmerilda Hitaj

    (University of Pavia)

  • Elisa Mastrogiacomo

    (Insubria University)

Abstract

A sensitivity analysis of the impact of cumulative prospect theory (CPT) parameters on a Mean/Risk efficient frontier is performed through a simulation procedure, assuming a Multivariate Variance Gamma distribution for log-returns. The optimal investment problem for an agent with CPT preferences is then investigated empirically, by considering different parameters’ combinations for the CPT utility function. Three different portfolios, one hedge fund and two equity portfolios are considered in this study, where the Modified Herfindahl index is used as a measure of portfolio diversification, while the Omega ratio and the Information ratio are used as measures of performance.

Suggested Citation

  • Giorgio Consigli & Asmerilda Hitaj & Elisa Mastrogiacomo, 2019. "Portfolio choice under cumulative prospect theory: sensitivity analysis and an empirical study," Computational Management Science, Springer, vol. 16(1), pages 129-154, February.
  • Handle: RePEc:spr:comgts:v:16:y:2019:i:1:d:10.1007_s10287-018-0333-x
    DOI: 10.1007/s10287-018-0333-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10287-018-0333-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10287-018-0333-x?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. Thorsten HENS & János MAYER, 2014. "Cumulative Prospect Theory and Mean Variance Analysis: A Rigorous Comparison," Swiss Finance Institute Research Paper Series 14-23, Swiss Finance Institute.
    2. Hitaj, Asmerilda & Zambruno, Giovanni, 2016. "Are Smart Beta strategies suitable for hedge fund portfolios?," Review of Financial Economics, Elsevier, vol. 29(C), pages 37-51.
    3. Yaari, Menahem E, 1987. "The Dual Theory of Choice under Risk," Econometrica, Econometric Society, vol. 55(1), pages 95-115, January.
    4. Asmerilda Hitaj & Giovanni Zambruno, 2018. "Portfolio Optimization Using Modified Herfindahl Constraint," International Series in Operations Research & Management Science, in: Giorgio Consigli & Silvana Stefani & Giovanni Zambruno (ed.), Handbook of Recent Advances in Commodity and Financial Modeling, chapter 0, pages 211-239, Springer.
    5. 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.
    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. Andrew J. Patton, 2004. "On the Out-of-Sample Importance of Skewness and Asymmetric Dependence for Asset Allocation," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 130-168.
    8. Nicholas Barberis & Ming Huang, 2008. "Stocks as Lotteries: The Implications of Probability Weighting for Security Prices," American Economic Review, American Economic Association, vol. 98(5), pages 2066-2100, December.
    9. Lionel Martellini & Volker Ziemann, 2010. "Improved Estimates of Higher-Order Comoments and Implications for Portfolio Selection," The Review of Financial Studies, Society for Financial Studies, vol. 23(4), pages 1467-1502, April.
    10. 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..
    11. Xue Dong He & Xun Yu Zhou, 2011. "Portfolio Choice Under Cumulative Prospect Theory: An Analytical Treatment," Management Science, INFORMS, vol. 57(2), pages 315-331, February.
    12. Quiggin, John, 1993. "Testing between Alternative Models of Choice under Uncertainty: Comment," Journal of Risk and Uncertainty, Springer, vol. 6(2), pages 161-164, April.
    13. Bernard, Carole & Ghossoub, Mario, 2009. "Static Portfolio Choice under Cumulative Prospect Theory," MPRA Paper 15446, University Library of Munich, Germany.
    14. Colin F. Camerer & Howard Kunreuther, 1989. "Decision processes for low probability events: Policy implications," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 8(4), pages 565-592.
    15. Enrico Giorgi & Thorsten Hens & János Mayer, 2007. "Computational aspects of prospect theory with asset pricing applications," Computational Economics, Springer;Society for Computational Economics, vol. 29(3), pages 267-281, May.
    16. Nicholas C. Barberis, 2013. "Thirty Years of Prospect Theory in Economics: A Review and Assessment," Journal of Economic Perspectives, American Economic Association, vol. 27(1), pages 173-196, Winter.
    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. Francesco Cesarone & Massimiliano Corradini & Lorenzo Lampariello & Jessica Riccioni, 2023. "A new behavioral model for portfolio selection using the Half-Full/Half-Empty approach," Papers 2312.10749, arXiv.org.
    2. Wencheng Yu & Shaobo Liu & Lili Ding, 2021. "Efficiency Evaluation and Selection Strategies for Green Portfolios under Different Risk Appetites," Sustainability, MDPI, vol. 13(4), pages 1-15, February.
    3. Sweksha Srivastava & Abha Aggarwal & Pooja Bansal, 2024. "Efficiency Evaluation of Assets and Optimal Portfolio Generation by Cross Efficiency and Cumulative Prospect Theory," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 129-158, January.
    4. Taras Bodnar & Dmytro Ivasiuk & Nestor Parolya & Wolfgang Schmid, 2023. "Multi-period power utility optimization under stock return predictability," Computational Management Science, Springer, vol. 20(1), pages 1-27, December.
    5. Massimiliano Kaucic & Filippo Piccotto & Gabriele Sbaiz & Giorgio Valentinuz, 2023. "Optimal Portfolio with Sustainable Attitudes under Cumulative Prospect Theory," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 13(4), pages 1-4.

    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. Chao Gong & Chunhui Xu & Ji Wang, 2018. "An Efficient Adaptive Real Coded Genetic Algorithm to Solve the Portfolio Choice Problem Under Cumulative Prospect Theory," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 227-252, June.
    2. De Giorgi, Enrico G. & Legg, Shane, 2012. "Dynamic portfolio choice and asset pricing with narrow framing and probability weighting," Journal of Economic Dynamics and Control, Elsevier, vol. 36(7), pages 951-972.
    3. Matteo Del Vigna, 2011. "Financial market equilibria with heterogeneous agents: CAPM and market segmentation," Working Papers - Mathematical Economics 2011-08, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    4. Bernard, Carole & Chen, Jit Seng & Vanduffel, Steven, 2015. "Rationalizing investors’ choices," Journal of Mathematical Economics, Elsevier, vol. 59(C), pages 10-23.
    5. 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.
    6. 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.
    7. Jaroslava Hlouskova & Jana Mikocziova & Rudolf Sivak & Peter Tsigaris, 2014. "Capital Income Taxation and Risk-Taking under Prospect Theory: The Continuous Distribution Case," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(5), pages 374-391, November.
    8. Bin Zou & Rudi Zagst, 2015. "Optimal Investment with Transaction Costs under Cumulative Prospect Theory in Discrete Time," Papers 1511.04768, arXiv.org, revised Nov 2016.
    9. Arvanitis, Stelios & Scaillet, Olivier & Topaloglou, Nikolas, 2020. "Spanning analysis of stock market anomalies under prospect stochastic dominance," Working Papers unige:134101, University of Geneva, Geneva School of Economics and Management.
    10. 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.
    11. Fortin, Ines & Hlouskova, Jaroslava & Tsigaris, Panagiotis, 2016. "The Consumption-Investment Decision of a Prospect Theory Household," Economics Series 322, Institute for Advanced Studies.
    12. Jakusch, Sven Thorsten, 2017. "On the applicability of maximum likelihood methods: From experimental to financial data," SAFE Working Paper Series 148, Leibniz Institute for Financial Research SAFE, revised 2017.
    13. Thomas Epper & Helga Fehr-Duda, 2012. "The missing link: unifying risk taking and time discounting," ECON - Working Papers 096, Department of Economics - University of Zurich, revised Oct 2018.
    14. Bi, Xiuchun & Cui, Zhenyu & Fan, Jiacheng & Yuan, Lvning & Zhang, Shuguang, 2023. "Optimal investment problem under behavioral setting: A Lagrange duality perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 156(C).
    15. Francesco Cesarone & Massimiliano Corradini & Lorenzo Lampariello & Jessica Riccioni, 2023. "A new behavioral model for portfolio selection using the Half-Full/Half-Empty approach," Papers 2312.10749, arXiv.org.
    16. Carolin Bock & Maximilian Schmidt, 2015. "Should I stay, or should I go? – How fund dynamics influence venture capital exit decisions," Review of Financial Economics, John Wiley & Sons, vol. 27(1), pages 68-82, November.
    17. Chi, Yichun & Zheng, Jiakun & Zhuang, Shengchao, 2022. "S-shaped narrow framing, skewness and the demand for insurance," Insurance: Mathematics and Economics, Elsevier, vol. 105(C), pages 279-292.
    18. Matthew D. Rablen, 2023. "Loss Aversion, Risk Aversion, and the Shape of the Probability Weighting Function," Working Papers 2023013, The University of Sheffield, Department of Economics.
    19. Alexander L. Brown & Taisuke Imai & Ferdinand M. Vieider & Colin F. Camerer, 2024. "Meta-analysis of Empirical Estimates of Loss Aversion," Journal of Economic Literature, American Economic Association, vol. 62(2), pages 485-516, June.
    20. Georgalos, Konstantinos & Paya, Ivan & Peel, David A., 2021. "On the contribution of the Markowitz model of utility to explain risky choice in experimental research," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 527-543.

    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:comgts:v:16:y:2019:i:1:d:10.1007_s10287-018-0333-x. 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.