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On the optimal use of put options under trade restrictions

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  • Bell, Peter N

Abstract

Consider an agent who holds a stock, but is allowed to buy and hold some quantity of at-the-money put options on the stock. Such an agent must decide the optimal use of financial derivatives under trade restrictions. This paper uses simulation to compare the optimal quantity when the agent maximizes mean-variance utility or Value at Risk over wealth at option expiry. The optimal quantity is larger than the stock holding under mean-variance utility and precisely the same under value at risk. The options do not remove all variation in returns but still benefit the agent.

Suggested Citation

  • Bell, Peter N, 2014. "On the optimal use of put options under trade restrictions," MPRA Paper 62155, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:62155
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    References listed on IDEAS

    as
    1. Robert A. Jarrow & Dilip B. Madan, 1997. "Is Mean-Variance Analysis Vacuous: Or was Beta Still Born?," Review of Finance, European Finance Association, vol. 1(1), pages 15-30.
    2. Thierry Post & Martijn J. van den Assem & Guido Baltussen & Richard H. Thaler, 2008. "Deal or No Deal? Decision Making under Risk in a Large-Payoff Game Show," American Economic Review, American Economic Association, vol. 98(1), pages 38-71, March.
    3. Liu, Jun & Pan, Jun, 2003. "Dynamic derivative strategies," Journal of Financial Economics, Elsevier, vol. 69(3), pages 401-430, September.
    4. Basak, Suleyman & Shapiro, Alexander, 2001. "Value-at-Risk-Based Risk Management: Optimal Policies and Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 14(2), pages 371-405.
    5. MOSSIN, Jan, 1968. "Aspects of rational insurance purchasing," LIDAM Reprints CORE 23, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Gregory W. Brown & Klaus Bjerre Toft, 2002. "How Firms Should Hedge," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1283-1324.
    7. Keith H. Coble & Barry J. Barnett, 2013. "Why Do We Subsidize Crop Insurance?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(2), pages 498-504.
    8. Markowitz, Harry, 2014. "Mean–variance approximations to expected utility," European Journal of Operational Research, Elsevier, vol. 234(2), pages 346-355.
    9. Griselda Deelstra & Michèle Vanmaele & David Vyncke, 2010. "Minimizing the Risk of a Financial Product Using a Put Option," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 77(4), pages 767-800, December.
    10. Bettis, J. Carr & Bizjak, John M. & Lemmon, Michael L., 2001. "Managerial Ownership, Incentive Contracting, and the Use of Zero-Cost Collars and Equity Swaps by Corporate Insiders," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 36(3), pages 345-370, September.
    11. Dong‐Hyun Ahn & Jacob Boudoukh & Matthew Richardson & Robert F. Whitelaw, 1999. "Optimal Risk Management Using Options," Journal of Finance, American Finance Association, vol. 54(1), pages 359-375, February.
    12. P. Carr & D. Madan, 2001. "Optimal positioning in derivative securities," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 19-37.
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    More about this item

    Keywords

    Portfolio optimization; put option; trade restrictions; simulation.;
    All these keywords.

    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General
    • 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

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