Authors:
M. Delgado Calvo-Flores
1
;
J. F. Núñez Negrillo
1
;
E. Gibaja Galindo
2
and
C. Molina Férnandez
3
Affiliations:
1
E.T.S. de Ingeniería Informática, Universidad de Granada, Spain
;
2
Universidad de Córdoba, Spain
;
3
Universidad de Jaén, Spain
Keyword(s):
Significant variables, genetic algorithms, stock market.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Biomedical Engineering
;
Business Analytics
;
Data Engineering
;
Data Mining
;
Databases and Information Systems Integration
;
Datamining
;
Enterprise Information Systems
;
Evolutionary Programming
;
Health Information Systems
;
Industrial Applications of Artificial Intelligence
;
Information Systems Analysis and Specification
;
Knowledge Management
;
Ontologies and the Semantic Web
;
Sensor Networks
;
Signal Processing
;
Society, e-Business and e-Government
;
Soft Computing
;
Strategic Decision Support Systems
;
Web Information Systems and Technologies
Abstract:
Nowadays, stock market investment is governed by investment strategies. An investment strategy consists in following a fixed philosophy over a period of time, and it can have a scientific, statistical or merely heuristic base. No method currently exists which is capable of measuring how good an investment strategy is either objectively or realistically. Through the use of Artificial Intelligence and Data Mining tools we have studied the different investment strategies of an important Spanish management agency and extracted a series of significant characteristics to describe them. Our objective is to evaluate and compare investment strategies in order to be able to use those which produce a peak return in our investment.