Using GAs to balance technical indicators on stock picking for financial portfolio composition

Abstract

The building of financial portfolios or funds constitutes a widely known problematic in financial markets which normally requires a rigorous analysis in order to select the most profitable assets. This subject is becoming popular among computer scientists which try to adapt known Intelligent Computation techniques to the market's domain. The presented paper proposes a potential system, based on those techniques, which aims to generate a profitable portfolio by using technical analysis indicators. In order to validate the designed application we performed a comparison against the Buy & Hold strategy and a purely random one. The preliminary results are promising once; the developed approach easily beats the remaining methodologies during Bull Market periods.