IDEAS home Printed from https://ideas.repec.org/a/taf/quantf/v14y2014i1p143-170.html
   My bibliography  Save this article

Option pricing with realistic ARCH processes

Author

Listed:
  • Gilles Zumbach
  • Luis Fern�ndez

Abstract

This paper presents a complete computation of option prices based on a realistic process for the underlying and on the construction of a risk-neutral measure as induced by a no-arbitrage replication strategy. The underlying is modelled with a long-memory ARCH process, with relative returns, fat-tailed innovations and multi-scale leverage. The process parameters are estimated on the SP500 stock index (in the physical measure). The change of measure from to the risk-neutral measure is derived rigorously along each path drawn from the process, yielding a Radon--Nikodym derivative for a given choice of a risk aversion function. A small expansion allows to compute explicitly this change of measure. Finally, a given European option's price is obtained as the expectation in of the discounted payoff with a weight given by the change of measure . This procedure is implemented in a Monte Carlo simulation, and allows to compute the option prices, without further adjustable parameters. The computed implied volatility surfaces are compared with empirical surfaces based on European put and call options on the SP500 from 1996 to 2010. Our pricing scheme is able to reproduce the level, the smile, the smirk and the term structure of the surfaces, without any calibration on the observed option prices. We discuss the respective roles of the and measures, the distribution of the terminal prices in both measures, the small impact of the risk aversion and drift premium, and finally we suggest simplifications of our pricing scheme for practical purposes.

Suggested Citation

  • Gilles Zumbach & Luis Fern�ndez, 2014. "Option pricing with realistic ARCH processes," Quantitative Finance, Taylor & Francis Journals, vol. 14(1), pages 143-170, January.
  • Handle: RePEc:taf:quantf:v:14:y:2014:i:1:p:143-170
    DOI: 10.1080/14697688.2013.816437
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/14697688.2013.816437
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/14697688.2013.816437?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.

    Citations

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


    Cited by:

    1. Pier Francesco Procacci & Tomaso Aste, 2018. "Forecasting market states," Papers 1807.05836, arXiv.org, revised May 2019.
    2. Pooja Gupta & Angshul Majumdar & Emilie Chouzenoux & Giovanni Chierchia, 2020. "SuperDeConFuse: A Supervised Deep Convolutional Transform based Fusion Framework for Financial Trading Systems," Papers 2011.04364, arXiv.org.

    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:taf:quantf:v:14:y:2014:i:1:p:143-170. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RQUF20 .

    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.