Optimization of technical rules by genetic algorithms: evidence from the Madrid stock market

Fernando Fernandez-Rodriguez, Christian Gonzalez-Martel () and Simon Sosvilla-Rivero

Applied Financial Economics, 2005, vol. 15, issue 11, 773-775

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.

Date: 2005
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/09603100500107818 (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Optimisation of Technical Rules by Genetic Algorithms: Evidence from the Madrid Stock Market
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:apfiec:v:15:y:2005:i:11:p:773-775

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAFE20

DOI: 10.1080/09603100500107818

Access Statistics for this article

Applied Financial Economics is currently edited by Anita Phillips

More articles in Applied Financial Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().