Pricing Derivatives by Path Integral and Neural Networks
arXiv:cond-mat/0211260 · doi:10.1016/S0378-4371(02)01907-6
Abstract
Recent progress in the development of efficient computational algorithms to price financial derivatives is summarized. A first algorithm is based on a path integral approach to option pricing, while a second algorithm makes use of a neural network parameterization of option prices. The accuracy of the two methods is established from comparisons with the results of the standard procedures used in quantitative finance.
7 pages, 1 figure, 1 table. Contribution to Proceedings of International Econophysics Conference, Bali, August 28-31, 2002