Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/49192
Title: On the profitability of technical trading rules based on artificial neural networks:: Evidence from the Madrid stock market
Authors: Fernández-Rodríguez, Fernando 
González-Martel, Christian 
Sosvilla-Rivero, Simón
Keywords: Security Returns
Issue Date: 2000
Publisher: 0165-1765
Journal: Economics Letters 
Abstract: 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
Source: Economics Letters[ISSN 0165-1765],v. 69, p. 89-94
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