Pricing Derivatives by Path Integral and Neural Networks
Statistical Mechanics
2009-11-07 v1 Disordered Systems and Neural Networks
Pricing of Securities
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.
Cite
@article{arxiv.cond-mat/0211260,
title = {Pricing Derivatives by Path Integral and Neural Networks},
author = {G. Montagna and M. Morelli and O. Nicrosini and P. Amato and M. Farina},
journal= {arXiv preprint arXiv:cond-mat/0211260},
year = {2009}
}
Comments
7 pages, 1 figure, 1 table. Contribution to Proceedings of International Econophysics Conference, Bali, August 28-31, 2002