Pricing derivatives by path integral and neural networks

被引：10

作者：

Montagna, G

Morelli, M

Nicrosini, O

Amato, P

Farina, M

机构：

[1] Univ Pavia, Dipartimento Fis Nucl & Teor, I-27100 Pavia, Italy

[2] Ist Nazl Fis Nucl, Sez Pavia, I-27100 Pavia, Italy

[3] ST Microelect Softcomp Nanoorgan Silicon Opt Micr, Milan, Italy

来源：

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS | 2003年 / 324卷 / 1-2期

关键词：

econophysics; option pricing; path integral; neural networks;

D O I：

10.1016/S0378-4371(02)01907-6

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

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. (C) 2002 Elsevier Science B.V. All rights reserved.

引用

页码：189 / 195

页数：7

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