Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/270073 
Year of Publication: 
2021
Citation: 
[Journal:] Cogent Economics & Finance [ISSN:] 2332-2039 [Volume:] 9 [Issue:] 1 [Article No.:] 1914285 [Year:] 2021 [Pages:] 1-15
Publisher: 
Taylor & Francis, Abingdon
Abstract: 
In this paper, a feed-forward artificial neural network (ANN) is used to price Johannesburg Stock Exchange (JSE) Top 40 European call options using a constructed implied volatility surface. The prices generated by the ANN were compared to the prices obtained using the Black-Scholes (BS) model. It was found that the pricing performance of the ANN significantly improves when the number of training samples are increased and that ANNs are able to price European call options in the South African market with a high degree of accuracy.
Subjects: 
Artificial intelligence
European call options
financial derivatives
implied volatility
Johannesburg Stock Exchange (JSE)
machine learning
neural networks
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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