IDEAS home Printed from https://ideas.repec.org/a/wsi/qjfxxx/v04y2014i03ns2010139214500153.html
   My bibliography  Save this article

Why Are Put Options So Expensive?

Author

Listed:
  • Oleg Bondarenko

    (Department of Finance (MC 168), University of Illinois at Chicago, 601 S. Morgan St., Chicago, IL 60607, USA)

Abstract

This paper studies the "overpriced puts puzzle" — the finding that historical prices of the S&P 500 put options have been too high and incompatible with the canonical asset-pricing models. To investigate whether put returns could be rationalized by another, possibly non-standard equilibrium model, we implement the model-free methodology of Bondarenko [2003a, Statistical Arbitrage and Securities Prices,Review of Financial Studies16, 875–919]. The methodology requires no parametric assumptions on investors' preferences. Furthermore, it can be applied even when the sample is affected by certain selection biases (such as the Peso problem) and when investors' beliefs are incorrect. The main finding of the paper is thatnomodel within a studied class of models can possibly explain the put anomaly.

Suggested Citation

  • Oleg Bondarenko, 2014. "Why Are Put Options So Expensive?," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 4(03), pages 1-50.
    • Handle: RePEc:wsi:qjfxxx:v:04:y:2014:i:03:n:s2010139214500153
    DOI: 10.1142/S2010139214500153
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S2010139214500153
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S2010139214500153?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 search for a different version of it.

    More about this item

    Keywords

    Market efficiency hypothesis; rational learning; option valuation; risk-neutral density; peso problem; JEL Classification: G12; JEL Classification: G13; JEL Classification: G14;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:wsi:qjfxxx:v:04:y:2014:i:03:n:s2010139214500153. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/qjf/qjf.shtml .

    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.