Application of sensitivity analysis to neural network determination of financial variable relationships

被引：0

作者：

Gillespie, ES ^{[1
]}

Wilson, RN ^{[1
]}

机构：

[1] Univ Ulster, Coleraine BT5Z 1SA, Londonderry, North Ireland

来源：

APPLIED STOCHASTIC MODELS AND DATA ANALYSIS | 1997年 / 13卷 / 3-4期

关键词：

neural networks; financial variables; principal components; adaptive learning rates;

D O I：

10.1002/(SICI)1099-0747(199709/12)13:3/4<409::AID-ASM335>3.0.CO;2-V

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

This paper considers the application of artificial neural networks to determine the relationships between the bond rating of the financial variables of the major companies of the U.S.A. Owing to the high correlation between some of the financial variables, the inputs to the neural network are in principal component form. A pattern of limiting sensitivity has been found. (C) 1998 John Wiley & Sons, Ltd.

引用

页码：409 / 414

页数：6

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