Title :
Tradinnova-LCS: Dynamic stock portfolio decision-making assistance model with genetic based machine learning
Author :
Casanova, Isidoro J.
Author_Institution :
Dept. of Inf. & Syst., Univ. of Murcia, Murcia, Spain
Abstract :
This paper describes a decision system based on rules for the management of a stock portfolio using a mechanism of dynamic learning to select the stocks to be incorporated. This system simulates the intelligent behavior of an investor, carrying out the buying and selling of stocks, such that during each day the best stocks will be selected to be incorporated in the portfolio by reinforcement learning with genetic programming. The system has been tested in 3 time periods (1 year, 3 years and 5 years), simulating the purchase/sale of stocks in the Spanish continuous market and the results have been compared with the revaluations obtained by the best investment funds operating in Spain.
Keywords :
decision making; financial management; genetic algorithms; learning (artificial intelligence); stock markets; Tradinnova-LCS; decision-making assistance model; dynamic learning; dynamic stock portfolio; genetic based machine learning; genetic programming; learning classifier system; reinforcement learning; Biological cells; Indexes; Investments; Marketing and sales; Portfolios; Resource management; Stock markets;
Conference_Titel :
Evolutionary Computation (CEC), 2010 IEEE Congress on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6909-3
DOI :
10.1109/CEC.2010.5586067
