Optimisation of Technical Rules by Genetic Algorithms: Evidence from the Madrid Stock Market

Fernando Fernández-Rodríguez, Christian Gonzalez-Martel () and Simon Sosvilla-Rivero

No 2001-14, Working Papers from FEDEA

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.

New Economics Papers: this item is included in nep-cmp and nep-evo
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://documentos.fedea.net/pubs/dt/2001/dt-2001-14.pdf (application/pdf)

Related works:
Journal Article: Optimization of technical rules by genetic algorithms: evidence from the Madrid stock market (2005)
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:fda:fdaddt:2001-14

Access Statistics for this paper

More papers in Working Papers from FEDEA
Bibliographic data for series maintained by Carmen Arias ().