A neural network approach to mutual fund net asset value forecasting

被引：102

作者：

Chiang, WC ^{[1
]}

Urban, TL ^{[1
]}

Baldridge, GW ^{[1
]}

机构：

[1] WORLDCOM INC,TULSA,OK

来源：

OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE | 1996年 / 24卷 / 02期

关键词：

forecasting; neural networks; mutual funds;

D O I：

10.1016/0305-0483(95)00059-3

中图分类号：

C93 [管理学];

学科分类号：

12 ; 1201 ; 1202 ; 120202 ;

摘要：

In this paper, an artificial neural network method is applied to forecast the end-of-year net asset value (NAV) of mutual funds. The back-propagation neural network is identified and explained. Historical economic information is used for the prediction of NAV data. The results of the forecasting are compared to those of traditional econometric techniques (i.e. linear and nonlinear regression analysis), and it Is shown that neural networks significantly outperform regression models in situations with limited data availability, Copyright (C) 1996 Elsevier Science Ltd

引用

页码：205 / 215

页数：11

共 39 条

[1]

Bansal A., 1993, Journal of Management Information Systems, V10, P11

[2] CHANCE CONSTRAINED PROGRAMMING APPROACH TO EMPIRICAL ANALYSES OF MUTUAL FUND INVESTMENT STRATEGIES [J].