IDEAS home Printed from https://ideas.repec.org/p/byu/byumcl/201208.html
   My bibliography  Save this paper

Option Pricing and Distribution Characteristics

Author

Listed:
  • David J. Mauler

    () (Department of Economics, Brigham Young University)

  • James B. McDonald

    () (Department of Economics, Brigham Young University)

Abstract

A number of flexible distributions (generalized beta of the second kind, inverse hyperbolic sine, g-and-h, Weibull, Burr-3, Burr-12, generalized gamma) are examined in the setting of option-pricing to explore potential improvements over the standard assumption of lognormal returns. Price formulas are presented specific to each assumed distributional form. The IHS option price formula has not previously been presented in the literature. An empirical application follows where implied risk-neutral density functions for each distribution are estimated from options on the S&P 500 Index. The distributions' performance relative to one another is then evaluated, with the GB2 appearing to be the most attractive choice.

Suggested Citation

  • David J. Mauler & James B. McDonald, 2012. "Option Pricing and Distribution Characteristics," BYU Macroeconomics and Computational Laboratory Working Paper Series 2012-08, Brigham Young University, Department of Economics, BYU Macroeconomics and Computational Laboratory.
  • Handle: RePEc:byu:byumcl:201208
    as

    Download full text from publisher

    File URL: http://economics.byu.edu/Documents/Macro%20Lab/Working%20Paper%20Series/BYUMCL2012-08.pdf
    File Function: First version, 2012
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Kabir K. Dutta & David F. Babbel, 2005. "Extracting Probabilistic Information from the Prices of Interest Rate Options: Tests of Distributional Assumptions," The Journal of Business, University of Chicago Press, vol. 78(3), pages 841-870, May.
    2. Charles J. Corrado, 2001. "Option pricing based on the generalized lambda distribution," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(3), pages 213-236, March.
    3. Milevsky, Moshe Arye & Posner, Steven E., 1998. "Asian Options, the Sum of Lognormals, and the Reciprocal Gamma Distribution," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 33(03), pages 409-422, September.
    4. McDonald, James B. & Turley, Patrick, 2011. "Distributional Characteristics: Just a Few More Moments," The American Statistician, American Statistical Association, vol. 65(2), pages 96-103.
    5. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    6. Frank Fabozzi & Radu Tunaru & George Albota, 2009. "Estimating risk-neutral density with parametric models in interest rate markets," Quantitative Finance, Taylor & Francis Journals, vol. 9(1), pages 55-70.
    7. Jackwerth, Jens Carsten & Rubinstein, Mark, 1996. " Recovering Probability Distributions from Option Prices," Journal of Finance, American Finance Association, vol. 51(5), pages 1611-1632, December.
    8. James B. Mcdonald & Jeff Sorensen & Patrick A. Turley, 2013. "Skewness And Kurtosis Properties Of Income Distribution Models," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 59(2), pages 360-374, June.
    9. Bruce J. Sherrick & Philip Garcia & Viswanath Tirupattur, 1996. "Recovering probabilistic information from option markets: Tests of distributional assumptions," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 16(5), pages 545-560, August.
    10. Bates, David S., 2000. "Post-'87 crash fears in the S&P 500 futures option market," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 181-238.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Option Pricing; Implied Distributions; Generalized Distributions;

    JEL classification:

    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General

    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:byu:byumcl:201208. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Kerk Phillips). General contact details of provider: http://edirc.repec.org/data/debyuus.html .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.