Machine Learning and Options Pricing: a Comparison of Black-Scholes and a Deep Neural Network in Pricing and Hedging DAX 30 Index Options
Year: 2017
Type: dissertation
Abstract: In this paper I study whether a deep feedforward network model performs better than the Black- Scholes model in pricing and delta hedging European-style call options. I apply the methodologies from selected original works on daily prices of call options written on DAX 30 between years 2013 and 2017. My results are mostly consistent with earlier literature and they indicate that the out-of- sample pricing performance of the neural network is superior to Black-Scholes with medium-term and long-term maturities and the out-of-sample delta-hedging performance of the neural network is superior with out-of-the-money options.
Source: Aaltodoc (Aalto University)
Author: Lauri Stark
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2883127593