On the profitability of technical trading rules based on artificial neural networks:: Evidence from the Madrid stock market

被引：115

作者：

Fernández-Rodríguez, F

González-Martel, C

Sosvilla-Rivero, S

机构：

[1] Univ Complutense Madrid, Madrid 28001, Spain

[2] Univ Las Palmas Gran Canaria, Las Palmas Gran Canaria, Spain

来源：

ECONOMICS LETTERS | 2000年 / 69卷 / 01期

关键词：

technical trading rules; neural network models; security markets;

D O I：

10.1016/S0165-1765(00)00270-6

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

In this paper we investigate the profitability of a simple technical trading rule based on Artificial Neural Networks (ANNs). Our results, based on applying this investment strategy to the General Index of the Madrid Stock Market, suggest that, in absence of trading costs, the technical trading rule is always superior to a buy-and-hold strategy for both "bear" market and "stable" market episodes. On the other hand, we find that the buy-and-hold strategy generates higher returns than the trading rule based on ANN only for a "bull" market subperiod. (C) 2000 Elsevier Science S.A. All rights reserved.

引用

页码：89 / 94

页数：6

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