Three-Layer Artificial Neural Network for Pricing Multi-Asset European Option

被引:1
|
作者
Zhou, Zhiqiang [1 ]
Wu, Hongying [2 ]
Li, Yuezhang [1 ]
Kang, Caijuan [1 ]
Wu, You [1 ]
机构
[1] Xiangnan Univ, Sch Econ & Management, Chenzhou 423000, Peoples R China
[2] Xiangnan Univ, Sch Math & Informat Sci, Chenzhou 423000, Peoples R China
基金
中国国家自然科学基金;
关键词
multi-asset option; European option; high-dimensional PDE; artificial neural network; three layers; RADIAL BASIS FUNCTION; LAPLACE TRANSFORM METHODS; BASIS FUNCTION PARTITION; CONTOUR INTEGRAL METHOD; MODEL; PDES;
D O I
10.3390/math12172770
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This paper studies an artificial neural network (ANN) for multi-asset European options. Firstly, a simple three-layer ANN-3 is established with undetermined weights and bias. Secondly, the time-space discrete PDE of the multi-asset option is given and the corresponding discrete data are fed into the ANN-3. Then, using least squares error as the objective function, the weights and bias of ANN-3 are trained well. Numerical examples are carried out to confirm the stability, accuracy and efficiency. Experiments show the ANN's relative error is about 0.8%. This method can be extended into multi-layer ANN-q(q>3) and extended into American options.
引用
收藏
页数:22
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