IDEAS home Printed from https://ideas.repec.org/a/wsi/afexxx/v09y2014i03ns2010495214500067.html
   My bibliography  Save this article

Analysis Of Market Volatility Via A Dynamically Purified Option Price Process

Author

Listed:
  • CHUONG LUONG

    (Department of Mathematics & Statistics, Curtin University, GPO Box U1987, Perth 6845, Western Australia, Australia)

  • NIKOLAI DOKUCHAEV

    (Department of Mathematics & Statistics, Curtin University, GPO Box U1987, Perth 6845, Western Australia, Australia)

Abstract

The paper studies methods of dynamic estimation of volatility for financial time series. We suggest to estimate the volatility as the implied volatility inferred from some artificial "dynamically purified" price process that in theory allows to eliminate the impact of the stock price movements. The complete elimination would be possible if the option prices were available for continuous sets of strike prices and expiration times. In practice, we have to use only finite sets of available prices. We discuss the construction of this process from the available option prices using different methods. In order to overcome the incompleteness of the available option prices, we suggests several interpolation approaches, including the first order Taylor series extrapolation and quadratic interpolation. We examine the potential of the implied volatility derived from this proposed process for forecasting of the future volatility, in comparison with the traditional implied volatility process such as the volatility index VIX.

Suggested Citation

  • Chuong Luong & Nikolai Dokuchaev, 2014. "Analysis Of Market Volatility Via A Dynamically Purified Option Price Process," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 9(03), pages 1-19.
    • Handle: RePEc:wsi:afexxx:v:09:y:2014:i:03:n:s2010495214500067
    DOI: 10.1142/S2010495214500067
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S2010495214500067
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S2010495214500067?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. Chuong Luong & Nikolai Dokuchaev, 2018. "Forecasting of Realised Volatility with the Random Forests Algorithm," JRFM, MDPI, vol. 11(4), pages 1-15, October.

    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:afexxx:v:09:y:2014:i:03:n:s2010495214500067. 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/afe/afe.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.