IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-16-00674.html
   My bibliography  Save this article

Optimization over a collection of decision trees with three-valued outcomes

Author

Listed:
  • Lonnie Turpin

    (McNeese State University)

  • Matiur Rahman

    (McNeese State University)

  • Alberto Marquez

    (Lamar University)

Abstract

This note considers decision trees with three-valued outcomes. The structure of the trees are represented in a familiar form, allowing for actions and states of nature where the states of nature are associated with objective probabilities. We discuss the partitioning of trees by path enumeration, and present a simple formula for calculating the probabilities of outcomes. Finally, we construct a linear programming model to optimize over the given probabilities to select the optimal partition tree representing the collection of actions that minimizes the potential for loss.

Suggested Citation

  • Lonnie Turpin & Matiur Rahman & Alberto Marquez, 2016. "Optimization over a collection of decision trees with three-valued outcomes," Economics Bulletin, AccessEcon, vol. 36(4), pages 1959-1965.
  • Handle: RePEc:ebl:ecbull:eb-16-00674
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/Pubs/EB/2016/Volume36/EB-16-V36-I4-P191.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Dilip Soman & Amar Cheema, 2002. "The Effect of Credit on Spending Decisions: The Role of the Credit Limit and Credibility," Marketing Science, INFORMS, vol. 21(1), pages 32-53, September.
    3. Nygren, Thomas E. & Isen, Alice M. & Taylor, Pamela J. & Dulin, Jessica, 1996. "The Influence of Positive Affect on the Decision Rule in Risk Situations: Focus on Outcome (and Especially Avoidance of Loss) Rather Than Probability," Organizational Behavior and Human Decision Processes, Elsevier, vol. 66(1), pages 59-72, April.
    4. Klaus Walde, 2008. "Applied Intertemporal Optimization," Books, Business School - Economics, University of Glasgow, number econ1.
    5. Kobberling, Veronika & Wakker, Peter P., 2005. "An index of loss aversion," Journal of Economic Theory, Elsevier, vol. 122(1), pages 119-131, May.
    Full references (including those not matched with items on IDEAS)

    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. Heiko Karle & Georg Kirchsteiger & Martin Peitz, 2015. "Loss Aversion and Consumption Choice: Theory and Experimental Evidence," American Economic Journal: Microeconomics, American Economic Association, vol. 7(2), pages 101-120, May.
    2. Martín Egozcue & Sébastien Massoni & Wing-Keung Wong & RiÄ ardas Zitikis, 2012. "Integration-segregation decisions under general value functions: "Create your own bundle — choose 1, 2, or all 3!"," Documents de travail du Centre d'Economie de la Sorbonne 12057, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    3. Bin Zou, 2017. "Optimal Investment In Hedge Funds Under Loss Aversion," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(03), pages 1-32, May.
    4. Luís Santos-Pinto & Adrian Bruhin & José Mata & Thomas Åstebro, 2015. "Detecting heterogeneous risk attitudes with mixed gambles," Theory and Decision, Springer, vol. 79(4), pages 573-600, December.
    5. Enrico G. De Giorgi & Thierry Post, 2011. "Loss Aversion with a State-Dependent Reference Point," Management Science, INFORMS, vol. 57(6), pages 1094-1110, June.
    6. D. A. Peel & Jie Zhang & D. Law, 2008. "The Markowitz model of utility supplemented with a small degree of probability distortion as an explanation of outcomes of Allais experiments over large and small payoffs and gambling on unlikely outc," Applied Economics, Taylor & Francis Journals, vol. 40(1), pages 17-26.
    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. Peters, Hans, 2012. "A preference foundation for constant loss aversion," Journal of Mathematical Economics, Elsevier, vol. 48(1), pages 21-25.
    9. Attema, Arthur E. & Brouwer, Werner B.F. & l’Haridon, Olivier & Pinto, Jose Luis, 2016. "An elicitation of utility for quality of life under prospect theory," Journal of Health Economics, Elsevier, vol. 48(C), pages 121-134.
    10. 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.
    11. Ahmad H. Juma’h & Yazan Alnsour, 2018. "Using Social Media Analytics: The Effect of President Trump’s Tweets On Companies’ Performance," Journal of Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, vol. 17(1), pages 100-121, March.
    12. Schunk, Daniel & Winter, Joachim, 2009. "The relationship between risk attitudes and heuristics in search tasks: A laboratory experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 71(2), pages 347-360, August.
    13. Pavlo Blavatskyy, 2021. "A simple non-parametric method for eliciting prospect theory's value function and measuring loss aversion under risk and ambiguity," Theory and Decision, Springer, vol. 91(3), pages 403-416, October.
    14. Ryan O. Murphy & Robert H. W. ten Brincke, 2018. "Hierarchical Maximum Likelihood Parameter Estimation for Cumulative Prospect Theory: Improving the Reliability of Individual Risk Parameter Estimates," Management Science, INFORMS, vol. 64(1), pages 308-328, January.
    15. Pramanik, Subhajit, 2021. "An Essay on Labor Supply Decisions and Reference Dependent Preferences," MPRA Paper 111499, University Library of Munich, Germany, revised 26 Dec 2021.
    16. Mohammed Abdellaoui & Olivier L'Haridon & Corina Paraschiv, 2011. "Experienced vs. Described Uncertainty: Do We Need Two Prospect Theory Specifications?," Management Science, INFORMS, vol. 57(10), pages 1879-1895, October.
    17. 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.
    18. Aurélien Baillon & Han Bleichrodt & Vitalie Spinu, 2020. "Searching for the Reference Point," Management Science, INFORMS, vol. 66(1), pages 93-112, January.
    19. Kpegli, Yao Thibaut & Corgnet, Brice & Zylbersztejn, Adam, 2023. "All at once! A comprehensive and tractable semi-parametric method to elicit prospect theory components," Journal of Mathematical Economics, Elsevier, vol. 104(C).
    20. Jiakun Zheng, 2020. "Optimal insurance design under narrow framing," Post-Print hal-04227370, HAL.

    More about this item

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

    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:ebl:ecbull:eb-16-00674. 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: John P. Conley (email available below). General contact details of provider: .

    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.