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The pricing of options on WIG20 using GARCH models

Author

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  • Szymon Kamiński

    (Faculty of Economic Sciences, University of Warsaw; Enterprise Risk Services, Deloitte Advisory)

Abstract

In this paper the application of several option pricing models has been tested on the basis of options traded on the Warsaw Stock Exchange. At first, theoretical option prices have been calculated according to the models chosen. Next, the models have been tested by comparing their option prices estimates to prices observed on the market. The models chosen are: a few alternative versions of the Duan (1995) GARCH Option Pricing Model, and two versions of the model by Black (1976). A separate section is devoted to the impact of the implied dividend yield on prices of options. The study covers a period from January 2006 to March 2012. Results show that the most accurate models are the Black model with a volatility term structure, and the Duan GARCH Option Pricing Model with implied dividend yield and Student's T random errors.

Suggested Citation

  • Szymon Kamiński, 2013. "The pricing of options on WIG20 using GARCH models," Working Papers 2013-06, Faculty of Economic Sciences, University of Warsaw.
  • Handle: RePEc:war:wpaper:2013-06
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    File URL: http://www.wne.uw.edu.pl/inf/wyd/WP/WNE_WP91.pdf
    File Function: First version, 2013
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    More about this item

    Keywords

    GARCH models; Duan methodology; Black model; implied volatility; option pricing;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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