Result: Improving technical trading systems by using a new MATLAB-based genetic algorithm procedure

Title:
Improving technical trading systems by using a new MATLAB-based genetic algorithm procedure
Authors:
PAPADAMOU, Stephanos, STEPHANIDES, George
Source:
Proceedings of the International Conference on Computational Methods in Sciences and Engineering 2004Mathematical and computer modelling. 46(1-2):189-197
Publisher Information:
Oxford: Elsevier Science, 2007.
Publication Year:
2007
Physical Description:
print, 26 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Mathematics, Mathématiques, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Analyse mathématique, Mathematical analysis, Calcul des variations et contrôle optimal, Calculus of variations and optimal control, Analyse numérique. Calcul scientifique, Numerical analysis. Scientific computation, Analyse numérique, Numerical analysis, Méthodes numériques en programmation mathématique, optimisation et calcul variationnel, Numerical methods in mathematical programming, optimization and calculus of variations, Méthodes de calcul scientifique (y compris calcul symbolique, calcul algébrique), Methods of scientific computing (including symbolic computation, algebraic computation), Algorithme génétique, Genetic algorithm, Algoritmo genético, Algorithme rapide, Fast algorithm, Algoritmo rápido, Analyse assistée, Computer aided analysis, Análisis asistido, Analyse numérique, Numerical analysis, Análisis numérico, Calcul scientifique, Scientific computation, Computación científica, Logiciel, Software, Logicial, Marché financier, Financial market, Mercado financiero, Mathématiques appliquées, Applied mathematics, Matemáticas aplicadas, Modèle mathématique, Mathematical model, Modelo matemático, Méthode optimisation, Optimization method, Método optimización, Programmation mathématique, Mathematical programming, Programación matemática, Stabilité numérique, Numerical stability, Estabilidad numérica, 49XX, 65Kxx, Financial markets, Genetic algorithms, Investment, Prediction, Technical rules
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Department ofEconomics, University of Thessaly, Argonauton and Filelinon, Volos, Greece
Department of Applied Informatics, University of Macedonia Economic and Social Sciences, Egnatias 156, Thessaloniki 54006, Greece
ISSN:
0895-7177
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=18794178
Rights:
Copyright 2007 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Mathematics
Accession Number:
edscal.18794178
Database:
PASCAL Archive

Further Information

Recent studies in financial markets suggest that technical analysis can be a very useful tool in predicting the trend. Trading systems are widely used for market assessment; however, parameter optimization of these systems has attracted little interest. In this paper, to explore the potential power of digital trading, we present a new MATLAB tool based on genetic algorithms; the tool specializes in parameter optimization of technical rules. It uses the power of genetic algorithms to generate fast and efficient solutions in real trading terms. Our tool was tested extensively on historical data of a UBS fund investing in emerging stock markets through our specific technical system. Results show that our proposed GATradeTool outperforms commonly used, non-adaptive, software tools with respect to the stability of return and time saving over the whole sample period. However, we provided evidence of a possible population size effect in quality of solutions.