Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/123177
Título: Thechnical Trading Rules in the Madrid Stock Market using Artificial Neural Networks
Autores/as: Fernández Rodríguez, Fernando 
González-Martel, Christian 
Clasificación UNESCO: 5302 Econometría
5303 Contabilidad económica
Palabras clave: Technical trading rules
Neural network models
Security markets
Fecha de publicación: 2000
Editor/a: Universidad de Las Palmas de Gran Canaria (ULPGC) 
Conferencia: International Conference on Modelling and Simulation (MS'2000) 
Resumen: In this paper we investígate the profitability of 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. In contrast, we find that the buy-and-hold strategy generates higher returns than the trading rule based on ANN for a "bull" market subperiod.
URI: http://hdl.handle.net/10553/123177
ISBN: 84-95286-59-9
Fuente: Proceedings of MS'2000 international conference on modelling and simulation / Ed. Rosario Berriel Martínez, p. 747-752
Colección:Actas de congresos
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