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.
| Author of HS Reutlingen | Herzog, 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: | Journal article |
| Language: | English |
| Publication year: | 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): |  Creative Commons - CC BY - Namensnennung 4.0 International |
