IDEAS home Printed from https://ideas.repec.org/a/wsi/ijtafx/v22y2019i06ns0219024919500286.html
   My bibliography  Save this article

Conditional Monte Carlo Scheme For Stable Greeks Of Worst-Of Autocallable Notes

Author

Listed:
  • FIRUZ RAKHMONOV

    (Model Risk Department, DOM.RF, 10 Vozdvizhenka, Moscow 125009, Russia)

  • PARVIZ RAKHMONOV

    (Deutsche Bank, London)

Abstract

It is well known that the application of Monte Carlo method in pricing of products with early termination feature results in a high Monte Carlo error and unstable greeks; see Fries & Joshi (2011). We develop a Monte Carlo scheme that utilizes a special structure of worst-of autocallable notes and produces stable greeks. This scheme clearly demonstrates the variance reduction in Monte Carlo scheme and can be used in pricing of multi-asset worst-of autocallable notes with any number of underlying assets. We suggest an algorithm and analyze its performance for an autocallable note on four assets. The suggested algorithm allows one to calculate stable greeks (delta, gamma, vega and others) and substantially reduce the computational effort to achieve the desired accuracy in comparison to standard Monte Carlo algorithm.

Suggested Citation

  • Firuz Rakhmonov & Parviz Rakhmonov, 2019. "Conditional Monte Carlo Scheme For Stable Greeks Of Worst-Of Autocallable Notes," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(06), pages 1-13, September.
    • Handle: RePEc:wsi:ijtafx:v:22:y:2019:i:06:n:s0219024919500286
    DOI: 10.1142/S0219024919500286
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219024919500286
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0219024919500286?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.

    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:ijtafx:v:22:y:2019:i:06:n:s0219024919500286. 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/ijtaf/ijtaf.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.