• DocumentCode
    585179
  • Title

    Islamic options pricing model via artificial neural network: “Benchmarking to Black-Scholes”

  • Author

    Adzhar, Z.A.A.K. ; Tafri, F.H.

  • Author_Institution
    Centre of Actuarial Studies, Univ. Teknol. Mara (UiTM) Shah Alam, Shah Alam, Malaysia
  • fYear
    2012
  • fDate
    10-12 Sept. 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Islamic finance industry has grown fast recently especially when Arab countries make huge investments with their oil money. The rapid growth has made the industry players search for a better risk management mechanism. This has led to the introduction of Islamic options based on urbun principle. Urbun defined as deposit to the sale purchase transaction has become popular as the most viable alternative to the conventional option. This research paper´s objective is to model Islamic options based on the urbun principles and shows how it can be differentiated from the conventional options. Artificial neural network has been popular recently for its application in pricing options; therefore it would be used in the research to price the Islamic option with Black-Scholes as its benchmarking. The result shows that artificial neural network is capable of pricing the Islamic options; however the lack of information provided by this model may be a concern.
  • Keywords
    ethical aspects; investment; microeconomics; neural nets; pricing; purchasing; Arab countries; Black-Scholes benchmarking; Islamic finance industry; Islamic options pricing model; artificial neural network; investments; oil money; risk management mechanism; sale purchase transaction deposit; urbun principle; Artificial Neural Network; Black-Scholes; Islamic Derivatives; Urbun;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Statistics in Science, Business, and Engineering (ICSSBE), 2012 International Conference on
  • Conference_Location
    Langkawi
  • Print_ISBN
    978-1-4673-1581-4
  • Type

    conf

  • DOI
    10.1109/ICSSBE.2012.6396562
  • Filename
    6396562