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Can genetic algorithms improve trading decisions in financial markets?

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Autor
Papadamou, S.; Stephanides, G.
Fecha
2005
Materia
Financial markets
Genetic algorithms
Non-linear technical rules
Prediction
Commerce
Computer simulation
Decision making
Evolutionary algorithms
Finance
Forecasting
Marketing
Optimization
Market assessment
Nonlinear technical rules
Trading systems
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Resumen
Over the last years, trading systems are widely used for market assessment however parameter optimization of these systems has adopted little concern. This paper, paper provides an answer to the question Can Genetic Algorithms Improve Trading Decisions in Financial Markets? Our proposed MATLAB based tool uses the power of genetic algorithms to generate fast and efficient solutions in real trading terms. By testing our trading system extensively on historical data of Emerging Stock markets we found that GATradeTool outperformed commonly used, non-adaptive, software tools with respect to the stability of return and time saving over the whole sample period.
URI
http://hdl.handle.net/11615/31654
Colecciones
  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ. [19735]
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