IDEAS home Printed from https://ideas.repec.org/a/aic/journl/y2009v56p197-201.html
   My bibliography  Save this article

Robust recovery of the risk neutral probability density from option prices

Author

Listed:
  • Gabriel Turinici

    (Université Paris Dauphine, Paris, France)

Abstract

We present in this paper a robust numerical procedure that allows extracting the risk neutral probability density data from a set of quoted European option prices. The procedure does not use any specific evolution model for the underlying; the probability density is the solution of a fitting problem to which we add a penalty term to ensure smoothness of the result. We give some examples from FOREX markets.

Suggested Citation

  • Gabriel Turinici, 2009. "Robust recovery of the risk neutral probability density from option prices," Analele Stiintifice ale Universitatii "Alexandru Ioan Cuza" din Iasi - Stiinte Economice (1954-2015), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 56, pages 197-201, November.
    • Handle: RePEc:aic:journl:y:2009:v:56:p:197-201
    as

    Download full text from publisher

    File URL: http://anale.feaa.uaic.ro/anale/resurse/17_F13_Turinici.pdf
    Download Restriction: no
    File URL: http://anale.feaa.uaic.ro/anale/en/Arhiva%202009%20Turinici/273
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gabriel TURINICI, 2008. "Local Volatility Calibration Using An Adjoint Proxy," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 2, pages 93-105, November.
    2. Gabriel Turinici, 2009. "Calibration of local volatility using the local and implied instantaneous variance," Post-Print hal-00338114, HAL.
    3. Gabriel Turinici, 2008. "Local volatility calibration using an adjoint proxy," Post-Print hal-00306187, HAL.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cristian Homescu, 2011. "Adjoints and Automatic (Algorithmic) Differentiation in Computational Finance," Papers 1107.1831, arXiv.org.
    2. F. Gerlich & A. Giese & J. Maruhn & E. Sachs, 2012. "Parameter identification in financial market models with a feasible point SQP algorithm," Computational Optimization and Applications, Springer, vol. 51(3), pages 1137-1161, April.

    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:aic:journl:y:2009:v:56:p:197-201. 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.

    If CitEc recognized a bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sireteanu Napoleon-Alexandru (email available below). General contact details of provider: https://edirc.repec.org/data/feaicro.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.