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Optimization of technical rules by genetic algorithms: evidence from the Madrid stock market
Authors:
Fernando Fern
ndez-Rodr
guez a;
Christian Gonzlez-Martel a;
Sim
n Sosvilla-Rivero b
ndez-Rodrguez a;
Christian Gonzlez-Martel a;
Simn Sosvilla-Rivero b
| Affiliations: | a Universidad de Las Palmas de Gran Canaria, |
| b FEDEA and Universidad Complutense de Madrid, 28040 Madrid, Spain |
DOI:
10.1080/09603100500107818
Publication Frequency:
24 issues per year
Subjects:
Economics;
Macroeconomics;
Number of References: 10
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Abstract
This paper investigates the profitability of a simple and very common technical trading rule applied to the General Index of the Madrid Stock Market. The optimal trading rule parameter values are found using a genetic algorithm. The results suggest that, for reasonable trading costs, the technical trading rule is always superior to a risk-adjusted buy-and-hold strategy.
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