IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/54394.html
   My bibliography  Save this paper

Optimal Use of Put Options in a Stock Portfolio

Author

Listed:
  • Peter N, Bell

Abstract

In this paper I consider a portfolio optimization problem where an agent holds an endowment of stock and is allowed to buy some quantity of a put option on the stock. This basic question (how much insurance to buy?) has been addressed in insurance economics through the literature on rational insurance purchasing. However, in contrast to the rational purchasing literature that uses exact algebraic analysis with a binomial probability model of portfolio value, I use numerical techniques to explore this problem. Numerical techniques allow me to approximate continuous probability distributions for key variables. Using large sample, asymptotic analysis I identify the optimal quantity of put options for three types of preferences over the distribution of portfolio value. The location of the optimal quantity varies across preferences and provides examples of important concepts from the rational purchasing literature: coinsurance for log utility (q* 1). I calculate the shape of the objective function and show the optimum is well defined for mean-variance utility and quantile-based preferences in an asymptotic setting. Using resampling, I show the optimal values are stable for the mean-variance utility and the quantile-based preferences but not the log utility. For the optimal value with mean-variance utility I show that the put option affects the probability distribution of portfolio value in an asymmetric way, which confirms that it is important to analyze the optimal use of derivatives in a continuous setting with numerical techniques.

Suggested Citation

  • Peter N, Bell, 2014. "Optimal Use of Put Options in a Stock Portfolio," MPRA Paper 54394, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:54394
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/54394/1/MPRA_paper_54394.pdf
    File Function: original version
    Download Restriction: no

    File URL: https://mpra.ub.uni-muenchen.de/54871/1/MPRA_paper_54871.pdf
    File Function: revised version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Briys, Eric P & Louberge, Henri, 1985. "On the Theory of Rational Insurance Purchasing: A Note," Journal of Finance, American Finance Association, vol. 40(2), pages 577-581, June.
    2. Razin, Assaf, 1976. "Rational Insurance Purchasing," Journal of Finance, American Finance Association, vol. 31(1), pages 133-137, March.
    3. MOSSIN, Jan, 1968. "Aspects of rational insurance purchasing," LIDAM Reprints CORE 23, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Ole Peters, 2010. "The time resolution of the St. Petersburg paradox," Papers 1011.4404, arXiv.org, revised Mar 2011.
    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. Bell, Peter Newton, 2014. "Design of Financial Derivatives: Statistical Power does not Ensure Risk Management Power," MPRA Paper 57438, University Library of Munich, Germany.
    2. Bell, Peter Newton, 2014. "Properties of time averages in a risk management simulation," MPRA Paper 55803, University Library of Munich, Germany.

    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. Yann Braouezec, 2015. "Public versus Private Insurance System with (and without) Transaction Costs: Optimal Segmentation Policy of an Informed monopolistPublic versus Private Insurance System with (and without) Transaction ," Working Papers 2013-ECO-23, IESEG School of Management, revised May 2014.
    2. Glenn W. Harrison & Jia Min Ng, 2016. "Evaluating The Expected Welfare Gain From Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 83(1), pages 91-120, January.
    3. Briys, Eric, 1987. "Demande d’assurance, décisions de consommation et de portefeuille : une analyse en temps continu," L'Actualité Economique, Société Canadienne de Science Economique, vol. 63(2), pages 200-212, juin et s.
    4. Emily Norman Zietz, 2003. "An Examination of the Demand for Life Insurance," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 6(2), pages 159-191, September.
    5. Henri Loubergé, 1998. "Risk and Insurance Economics 25 Years After," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 23(4), pages 540-567, October.
    6. Michael Braun & Alexander Muermann, 2004. "The Impact of Regret on the Demand for Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 71(4), pages 737-767, December.
    7. Thomas Eichner & Andreas Wagener, 2002. "Increases in Risk and the Welfare State," CESifo Working Paper Series 685, CESifo.
    8. Giovanni Millo & Gaetano Carmeci, 2011. "Non-life insurance consumption in Italy: a sub-regional panel data analysis," Journal of Geographical Systems, Springer, vol. 13(3), pages 273-298, September.
    9. Boonen, Tim J. & Liu, Fangda, 2022. "Insurance with heterogeneous preferences," Journal of Mathematical Economics, Elsevier, vol. 102(C).
    10. Amarante, Massimiliano & Ghossoub, Mario & Phelps, Edmund, 2015. "Ambiguity on the insurer’s side: The demand for insurance," Journal of Mathematical Economics, Elsevier, vol. 58(C), pages 61-78.
    11. DE DONDER, Philippe & PESTIEAU, Pierre, 2011. "Private, social and self insurance for long-term care: A political economy analysis," LIDAM Discussion Papers CORE 2011053, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. Ronny Klein, 2004. "Ansparen von Selbstbeteiligung in der Krankenversicherung?," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 73(4), pages 510-521.
    13. Marc A. Ragin & Benjamin L. Collier & Johannes G. Jaspersen, 2021. "The effect of information disclosure on demand for high‐load insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(1), pages 161-193, March.
    14. Toshihiro Ihori & Martin McGuire, 2010. "National self-insurance and self-protection against adversity: bureaucratic management of security and moral hazard," Economics of Governance, Springer, vol. 11(2), pages 103-122, April.
    15. Giora Harpaz, 1986. "Optimal Risk—Sharing Policies," The American Economist, Sage Publications, vol. 30(2), pages 37-40, October.
    16. Hoffmann, Sandra A. & Hanemann, W. Michael, 2005. "Torts and the Protection of "Legally Recognized" Interests," Discussion Papers 10472, Resources for the Future.
    17. Jing Ai & Lin Zhao & Wei Zhu, 2016. "Contracting with Present-Biased Consumers in Insurance Markets," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 41(2), pages 107-148, September.
    18. Xiaodong Du & Hongli Feng & David A. Hennessy, 2017. "Rationality of Choices in Subsidized Crop Insurance Markets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(3), pages 732-756.
    19. Schlesinger, Harris, 1999. "Decomposing catastrophic risk," Insurance: Mathematics and Economics, Elsevier, vol. 24(1-2), pages 95-101, March.
    20. Peter John Robinson & W. J. Wouter Botzen & Fujin Zhou, 2021. "An experimental study of charity hazard: The effect of risky and ambiguous government compensation on flood insurance demand," Journal of Risk and Uncertainty, Springer, vol. 63(3), pages 275-318, December.

    More about this item

    Keywords

    Portfolio; optimization; financial derivative; put option; quantity; expected utility; numerical analysis;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:pra:mprapa:54394. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.