IDEAS home Printed from https://ideas.repec.org/a/bla/finrev/v50y2015i1p27-56.html
   My bibliography  Save this article

Estimating Early Exercise Premiums on Gold and Copper Options Using a Multifactor Model and Density Matched Lattices

Author

Listed:
  • Jimmy E. Hilliard
  • Jitka Hilliard

Abstract

We use the standard geometric Brownian motion augmented by jumps to describe the spot underlying and mean regressive models of interest rates and convenience yields as state variables for gold and copper prices. Estimates of parameters of the diffusion processes are obtained by the Kalman filter. Using these estimates, jump parameters are estimated in the second stage by least squares. Early exercise premia on puts and calls are computed using a lattice with probabilities assigned by the density matching technique. We find that while deep in the money options have greater absolute early exercise premiums, the early exercise premium is roughly constant as a percent of option price. Our findings also confirm that gold behaves like an investment asset and copper behaves like a commodity.

Suggested Citation

  • Jimmy E. Hilliard & Jitka Hilliard, 2015. "Estimating Early Exercise Premiums on Gold and Copper Options Using a Multifactor Model and Density Matched Lattices," The Financial Review, Eastern Finance Association, vol. 50(1), pages 27-56, January.
  • Handle: RePEc:bla:finrev:v:50:y:2015:i:1:p:27-56
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/fire.12059
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Moreno, Manuel & Novales, Alfonso & Platania, Federico, 2019. "Long-term swings and seasonality in energy markets," European Journal of Operational Research, Elsevier, vol. 279(3), pages 1011-1023.
    2. Dong Zou & Pu Gong, 2017. "A Lattice Framework with Smooth Convergence for Pricing Real Estate Derivatives with Stochastic Interest Rate," The Journal of Real Estate Finance and Economics, Springer, vol. 55(2), pages 242-263, August.
    3. Tang, Chun-Hua, 2018. "Subjective value of the guarantees embedded in public cash-balance pension plans," Journal of Pension Economics and Finance, Cambridge University Press, vol. 17(2), pages 231-250, April.

    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:bla:finrev:v:50:y:2015:i:1:p:27-56. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/efaaaea.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.