Pricing derivatives by path integral and neural networks

Guido Montagna, Marco Morelli, Oreste Nicrosini, Paolo Amato and Marco Farina

Physica A: Statistical Mechanics and its Applications, 2003, vol. 324, issue 1, 189-195

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.

Keywords: Econophysics; Option pricing; Path integral; Neural networks (search for similar items in EconPapers)
Date: 2003
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:324:y:2003:i:1:p:189-195

DOI: 10.1016/S0378-4371(02)01907-6

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