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Reverse engineering of option pricing: an AI application

  • 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.

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Metadaten
Author of HS ReutlingenHerzog, Bodo; Osamah, Sufyan
URN:urn:nbn:de:bsz:rt2-opus4-24312
DOI:https://doi.org/10.3390/ijfs7040068
ISSN:2227-7072
Erschienen in:International journal of financial studies : open access journal
Publisher:MDPI
Place of publication:Basel
Document Type:Article
Language:English
Year of Publication:2019
Tag:artificial intelligence; derivatives; genetic algorithm; machine learning; option pricing; reverse engineering
Volume:7
Issue:4
Page Number:12
First Page:1
Last Page:12
Article Number:68
DDC classes:330 Wirtschaft
Open Access?:Ja
Licence (German):License Logo  Creative Commons - CC BY - Namensnennung 4.0 International