The option pricing model based on time values: an application of the universal approximation theory on unbounded domains

2019/10/02 by Qu, Yang, Wang, Ming-Xi
#Artificial Intelligence (cs.AI) #Computational Finance (q-fin.CP) #FOS: Computer and information sciences #FOS: Economics and business

paper · doi:10.48550/arxiv.1910.01490

Abstract

We propose a time value related decision function to treat a classical option pricing problem raised by Hutchinson-Lo-Poggio. In numerical experiments, the new decision function significantly improves the original model of Hutchinson-Lo-Poggio with faster convergence and better generalization performance. By proving a novel universal approximation theorem, we show that our decision function rather than Hutchinson-Lo-Poggio's can be approximated on the entire domain of definition by neural networks. Thus the experimental results are partially explained by the representation properties of networks.

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