Pricing vanilla options using artificial neural networks: Application to the South African market

被引：3
|
作者：
du Plooy, Ryno [1 ]
Venter, Pierre J. [1 ]
机构：
[1] Univ Johannesburg, Dept Finance & Investment Management, Auckland Pk, ZA-2006 Johannesburg, South Africa
来源：
COGENT ECONOMICS & FINANCE | 2021年 / 9卷 / 01期
关键词：
Artificial intelligence; European call options; financial derivatives; implied volatility; Johannesburg Stock Exchange ([!text type='JS']JS[!/text]E); machine learning; neural networks;
D O I：
10.1080/23322039.2021.1914285
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
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.
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页数：15
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