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Reverse Engineering of Option Pricing: An AI Application

Author

Listed:
  • Bodo Herzog

    (ESB Business School, Reutlingen University, Alteburgstr. 150, 72762 Reutlingen, Germany
    RRI Reutlingen Research Institute, 72762 Reutlingen, Germany)

  • Sufyan Osamah

    (ESB Business School, Reutlingen University, Alteburgstr. 150, 72762 Reutlingen, Germany)

Abstract
This paper studies option pricing based on a reverse engineering (RE) approach. We utilize artificial intelligence in order to numerically compute the prices of options. The data consist of more than 5000 call- and put-options from the German stock market. First, we find that option pricing under reverse engineering obtains a smaller root mean square error to market prices. Second, we show that the reverse engineering model is reliant on training data. In general, the novel idea of reverse engineering is a rewarding direction for future research. It circumvents the limitations of finance theory, among others strong assumptions and numerical approximations under the Black–Scholes model.

Suggested Citation

  • Bodo Herzog & Sufyan Osamah, 2019. "Reverse Engineering of Option Pricing: An AI Application," IJFS, MDPI, vol. 7(4), pages 1-12, November.
    • Handle: RePEc:gam:jijfss:v:7:y:2019:i:4:p:68-:d:284016
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    References listed on IDEAS

    as
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