Local Search Techniques for Constrained Portfolio SelectionProblems
Computational Economics
Technical market indicators optimization using evolutionary algorithms
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
A tree-based GA representation for the portfolio optimization problem
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Evolutionary Intelligence: An Introduction to Theory and Applications with Matlab
Evolutionary Intelligence: An Introduction to Theory and Applications with Matlab
Fitness function evaluation for MA trading strategies based on genetic algorithms
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Modesty is the best policy: automatic discovery of viable forecasting goals in financial data
EvoCOMNET'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part II
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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.