Artikel
A comparison of artificial neural networks and bootstrap aggregating ensembles in a modern financial derivative pricing framework
In this paper, the pricing performances of two learning networks, namely an artificial neural network and a bootstrap aggregating ensemble network, were compared when pricing the Johannesburg Stock Exchange (JSE) Top 40 European call options in a modern option pricing framework using a constructed implied volatility surface. In addition to this, the numerical accuracy of the better performing network was compared to a Monte Carlo simulation in a separate numerical experiment. It was found that the bootstrap aggregating ensemble network outperformed the artificial neural network and produced price estimates within the error bounds of a Monte Carlo simulation when pricing derivatives in a multi-curve framework setting.
- Language
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Englisch
- Bibliographic citation
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Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 14 ; Year: 2021 ; Issue: 6 ; Pages: 1-18 ; Basel: MDPI
- Classification
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Wirtschaft
- Subject
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artificial neural networks
collateral
funding
multi-curve framework
vanilla option pricing
- Event
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Geistige Schöpfung
- (who)
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Du Plooy, Ryno
Venter, Pierre J.
- Event
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Veröffentlichung
- (who)
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MDPI
- (where)
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Basel
- (when)
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2021
- DOI
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doi:10.3390/jrfm14060254
- Handle
- Last update
- 10.03.2025, 11:45 AM CET
Data provider
This object is provided by:
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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Du Plooy, Ryno
- Venter, Pierre J.
- MDPI
Time of origin
- 2021
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