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Artificial Neural Networks Performance in WIG20 Index Options Pricing

Author

Listed:
  • Maciej Wysocki

    (Quantitative Finance Research Group; Faculty of Economic Sciences, University of Warsaw)

  • Robert Ślepaczuk

    (Quantitative Finance Research Group; Faculty of Economic Sciences, University of Warsaw)

Abstract

In this paper the performance of artificial neural networks in option pricing is analyzed and compared with the results obtained from the Black – Scholes – Merton model based on the historical volatility. The results are compared based on various error metrics calculated separately between three moneyness ratios. The market data-driven approach is taken in order to train and test the neural network on the real-world data from the Warsaw Stock Exchange. The artificial neural network does not provide more accurate option prices. The Black – Scholes – Merton model turned out to be more precise and robust to various market conditions. In addition, the bias of the forecasts obtained from the neural network differs significantly between moneyness states.

Suggested Citation

  • Maciej Wysocki & Robert Ślepaczuk, 2020. "Artificial Neural Networks Performance in WIG20 Index Options Pricing," Working Papers 2020-19, Faculty of Economic Sciences, University of Warsaw.
    • Handle: RePEc:war:wpaper:2020-19
    as

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    File URL: https://www.wne.uw.edu.pl/index.php/download_file/5722/
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    option pricing; machine learning; artificial neural networks; implied volatility; supervised learning; index options; Black – Scholes – Merton model;
    All these keywords.

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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