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Open AccessArticle

Reverse Engineering of Option Pricing: An AI Application

by 1,2,* and 1
1
ESB Business School, Reutlingen University, Alteburgstr. 150, 72762 Reutlingen, Germany
2
RRI Reutlingen Research Institute, 72762 Reutlingen, Germany
*
Author to whom correspondence should be addressed.
Int. J. Financial Stud. 2019, 7(4), 68; https://doi.org/10.3390/ijfs7040068
Received: 30 August 2019 / Revised: 13 October 2019 / Accepted: 15 October 2019 / Published: 6 November 2019
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. View Full-Text
Keywords: reverse engineering; option pricing; derivatives; genetic algorithm; artificial intelligence; machine learning reverse engineering; option pricing; derivatives; genetic algorithm; artificial intelligence; machine learning
MDPI and ACS Style

Herzog, B.; Osamah, S. Reverse Engineering of Option Pricing: An AI Application. Int. J. Financial Stud. 2019, 7, 68. https://doi.org/10.3390/ijfs7040068

AMA Style

Herzog B, Osamah S. Reverse Engineering of Option Pricing: An AI Application. International Journal of Financial Studies. 2019; 7(4):68. https://doi.org/10.3390/ijfs7040068

Chicago/Turabian Style

Herzog, Bodo; Osamah, Sufyan. 2019. "Reverse Engineering of Option Pricing: An AI Application" Int. J. Financial Stud. 7, no. 4: 68. https://doi.org/10.3390/ijfs7040068

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