Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/49192
Título: On the profitability of technical trading rules based on artificial neural networks:: Evidence from the Madrid stock market
Autores/as: Fernández-Rodríguez, Fernando 
González-Martel, Christian 
Sosvilla-Rivero, Simón
Palabras clave: Security Returns
Fecha de publicación: 2000
Editor/a: 0165-1765
Publicación seriada: Economics Letters 
Resumen: 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.
URI: http://hdl.handle.net/10553/49192
ISSN: 0165-1765
Fuente: Economics Letters[ISSN 0165-1765],v. 69, p. 89-94
Colección:Artículos
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