@article{HerzogOsamah2019,
  author    = {Herzog, Bodo and Osamah, Sufyan},
  title     = {Reverse engineering of option pricing: an AI application},
  journal   = {International journal of financial studies : open access journal},
  volume    = {7},
  number    = {4},
  issn      = {2227-7072},
  doi       = {10.3390/ijfs7040068},
  institution = {ESB Business School},
  pages     = {68},
  year      = {2019},
  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.},
  language  = {en}
}