IDEAS home Printed from
   My bibliography  Save this article

Posouzení vybraných možností zefektivnění simulace Monte Carlo při opčním oceňování
[Examination of selected improvement approaches to Monte Carlo simulation in option pricing]


  • Tomáš Tichý


In general, there exist many ways to detect the fair value of financial derivatives. However, each of them is suitable for different purposes. For example, when the payoff function is not very simple or the underlying process is too complex, the approach of Monte Carlo simulation can be useful. Unfortunately, the plain Monte Carlo simulation needs a very high number of independent paths to get reliable results. It is the reason why an improvement of the plain approach should be applied to decrease the number of paths required in order to get reliable results. In this paper we study more closely several such approaches and examine their potential of increasing the efficiency. To be more exact, we apply the antithetic variates method and stratified sampling approaches, including their combinations in order to get the fair price of a plain vanilla call. We consider three distinct underlying processes: geometric Brownian motion, variance gamma model and normal inverse Gaussian model. We also verify the confidence interval for the option price. We did not find any improvements of examined methods for complex processes considering the definition via two or more independent random numbers. However, if the required accuracy is very high, it might be useful to apply the stratification to the distribution function of the complex process.

Suggested Citation

  • Tomáš Tichý, 2008. "Posouzení vybraných možností zefektivnění simulace Monte Carlo při opčním oceňování
    [Examination of selected improvement approaches to Monte Carlo simulation in option pricing]
    ," Politická ekonomie, University of Economics, Prague, vol. 2008(6), pages 772-794.
  • Handle: RePEc:prg:jnlpol:v:2008:y:2008:i:6:id:663:p:772-794

    Download full text from publisher

    File URL:
    Download Restriction: free of charge

    File URL:
    Download Restriction: free of charge

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item


    options; Simulation Monte Carlo; variance reduction methods; option pricing; Black and Scholes model; Lévy process; variance gamma model; normal inverse Gaussian model; confidence interval;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G2 - Financial Economics - - Financial Institutions and Services


    Access and download statistics


    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:prg:jnlpol:v:2008:y:2008:i:6:id:663:p:772-794. 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: (Frantisek Sokolovsky). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.