Advanced Search
MyIDEAS: Login

Improving Non-Parametric Option Pricing during the Financial Crisis

Contents:

Author Info

  • Dragan Kukolj

    ()
    (Faculty of Technical Sciences, University of Novi Sad, Serbia)

  • Nikola Gradojevic

    ()
    (Faculty of Business Administration, Lakehead University, Canada; The Rimini Centre for Economic Analysis, Italy)

  • Camillo Lento

    ()
    (Faculty of Business Administration, Lakehead University, Canada)

Abstract

Financial option prices have experienced excessive volatility in response to the recent economic and financial crisis. During the crisis periods, financial markets are, in general, subject to an abrupt regime shift which imposes a significant challenge to option pricing models. In this context, swiftly evolving markets and institutions require valuation models that are capable of recognizing and adapting to such changes. Both parametric and non-parametric pricing models have shown poor forecast ability for options traded in late 1987 and 2008. Surprisingly, the pricing inaccuracy was more pronounced for non-parametric models than for parametric models. To address this problem, we propose a modular neural network-fuzzy learning vector quantization (MNN-FLVQ) model that uses the Kohonen unsupervised learning and fuzzy clustering algorithms to classify the S&P 500 stock market index options, and thereby detect a regime shift. The results for the 2008 financial crisis demonstrate that the MNN-FLVQ model is superior to the competing methods in regards to option pricing during regime shifts

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://www.rcfea.org/RePEc/pdf/wp35_12.pdf
Download Restriction: no

Bibliographic Info

Paper provided by The Rimini Centre for Economic Analysis in its series Working Paper Series with number 35_12.

as in new window
Length:
Date of creation: Jun 2012
Date of revision:
Handle: RePEc:rim:rimwps:35_12

Contact details of provider:
Postal: Via Patara, 3, 47921 Rimini (RN)
Phone: +390541434142
Fax: +39054155431
Email:
Web page: http://www.rcfea.org
More information through EDIRC

Related research

Keywords:

This paper has been announced in the following NEP Reports:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Bates, David S., 2000. "Post-'87 crash fears in the S&P 500 futures option market," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 181-238.
  2. René Garcia & Ramazan Gençay, 1998. "Pricing and Hedging Derivative Securities with Neural Networks and a Homogeneity Hint," CIRANO Working Papers 98s-35, CIRANO.
  3. Nikola Gradojevic & Ramazan Gencay & Dragan Kukolj, 2009. "Option Pricing with Modular Neural Networks," Working Paper Series 32_09, The Rimini Centre for Economic Analysis, revised Jan 2009.
Full references (including those not matched with items on IDEAS)

Citations

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:rim:rimwps:35_12. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Roberto Patuelli).

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.