Reverse Engineering of Option Pricing: An AI Application

Bodo Herzog and Sufyan Osamah
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Sufyan Osamah: ESB Business School, Reutlingen University, Alteburgstr. 150, 72762 Reutlingen, Germany

IJFS, 2019, vol. 7, issue 4, 1-12

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.

Keywords: reverse engineering; option pricing; derivatives; genetic algorithm; artificial intelligence; machine learning (search for similar items in EconPapers)
JEL-codes: F2 F3 F41 F42 G1 G2 G3 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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