IDEAS home Printed from https://ideas.repec.org/a/ucp/jnlbus/v78y2005i3p841-870.html

Extracting Probabilistic Information from the Prices of Interest Rate Options: Tests of Distributional Assumptions

Author

Listed:
  • Kabir K. Dutta

    (Federal Reserve Bank of Boston)

  • David F. Babbel

    (Wharton School, University of Pennsylvania)

Abstract

Return distributions in general and interest rates in particular have been observed to exhibit skewness and kurtosis that cannot be explained by the (log)normal distribution. Using g-and-h distribution we derived a closed-form option pricing formula for pricing European options. We measured its performance using interest rate cap data and compared it with the option prices based on the lognormal, Burr-3, Weibull, and GB2 distributions. We observed that the g-and-h distribution exhibited a high degree of accuracy in pricing options, much better than those other distributions in extracting probabilistic information from the option market.

Suggested Citation

  • 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.
    • Handle: RePEc:ucp:jnlbus:v:78:y:2005:i:3:p:841-870
    DOI: 10.1086/429646
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1086/429646
    File Function: main text
    Download Restriction: Access to the online full text or PDF requires a subscription.
    File URL: https://libkey.io/10.1086/429646?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 look for a different version below or

    for a different version of it.

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Albrecht, Peter & Schwake, Edmund & Winter, Peter, 2007. "Quantifizierung operationeller Risiken: Der Loss Distribution Approach," German Risk and Insurance Review (GRIR), University of Cologne, Department of Risk Management and Insurance, vol. 3(1), pages 1-45.
    2. David Mauler & James McDonald, 2015. "Option Pricing and Distribution Characteristics," Computational Economics, Springer;Society for Computational Economics, vol. 45(4), pages 579-595, April.
    3. Eeckhoudt, Louis & Schlesinger, Harris, 2008. "Changes in risk and the demand for saving," Journal of Monetary Economics, Elsevier, vol. 55(7), pages 1329-1336, October.
    4. Kabir K. Dutta & David F. Babbel, 2002. "On Measuring Skewness and Kurtosis in Short Rate Distributions: The Case of the US Dollar London Inter Bank Offer Rates," Center for Financial Institutions Working Papers 02-25, Wharton School Center for Financial Institutions, University of Pennsylvania.
    5. Andreas A. Jobst, 2007. "It's all in the data – consistent operational risk measurement and regulation," Journal of Financial Regulation and Compliance, Emerald Group Publishing Limited, vol. 15(4), pages 423-449, November.
    6. José Renato Haas Ornelas & José Santiago Fajardo Barbachan & Aquiles Rocha de Farias, 2012. "Estimating Relative Risk Aversion, Risk-Neutral and Real-World Densities using Brazilian Real Currency Options," Working Papers Series 269, Central Bank of Brazil, Research Department.
    7. Xu, Yihuan & Iglewicz, Boris & Chervoneva, Inna, 2014. "Robust estimation of the parameters of g-and-h distributions, with applications to outlier detection," Computational Statistics & Data Analysis, Elsevier, vol. 75(C), pages 66-80.
    8. Sanjiv Jaggia & Alison Kelly-Hawke, 2009. "Modelling skewness and elongation in financial returns: the case of exchange-traded funds," Applied Financial Economics, Taylor & Francis Journals, vol. 19(16), pages 1305-1316.
    9. Fischer, Matthias J., 2006. "Generalized Tukey-type distributions with application to financial and teletraffic data," Discussion Papers 72/2006, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Statistics and Econometrics.
    10. José María Sarabia & Vanesa Jordá & Faustino Prieto & Montserrat Guillén, 2020. "Multivariate Classes of GB2 Distributions with Applications," Mathematics, MDPI, vol. 9(1), pages 1-21, December.
    11. José Renato Haas Ornelas & Marcelo Yoshio Takami, 2011. "Recovering Risk-Neutral Densities from Brazilian Interest Rate Options," Brazilian Review of Finance, Brazilian Society of Finance, vol. 9(1), pages 9-26.
    12. Marcos Massaki Abe & Eui Jung Chang & Benjamin Miranda Tabak, 2007. "Forecasting Exchange Rate Density Using Parametric Models: the Case of Brazil," Brazilian Review of Finance, Brazilian Society of Finance, vol. 5(1), pages 29-39.

    More about this item

    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:ucp:jnlbus:v:78:y:2005:i:3:p:841-870. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Journals Division (email available below). General contact details of provider: https://www.jstor.org/journal/jbusiness .

    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.