Beating the Best: A Neural Network Challenges the Black-Scholes Formula
Institute of Electrical and Electronics Engineers (IEEE)
Proceedings., Ninth Conference on Artificial Intelligence for Applications, 1993
A neural network model which processes financial input data is presented to estimate the market price of options. The network's ability to estimate option prices is compared to estimates generated by the Black-Scholes model, a traditional financial model. Comparisons reveal that the neural network outperforms the Black-Scholes model in about half of the cases examined. While the two modeling approaches differ fundamentally in their methodology for determining option prices, some common results emerge. While the neural network performs better than Black-Scholes on prices out-of-the-money, estimations near the expiration data are accurate for both.