Optimization of control parameters for genetic algorithms
IEEE Transactions on Systems, Man and Cybernetics
An introduction to genetic algorithms
An introduction to genetic algorithms
Adaptive Learning by Genetic Algorithms: Analytical Results and Applications to Economic Models
Adaptive Learning by Genetic Algorithms: Analytical Results and Applications to Economic Models
Physicists Attempt to Scale the Ivory Towers of Finance
Computing in Science and Engineering
Fractals and Scaling In Finance: Discontinuity, Concentration, Risk
Fractals and Scaling In Finance: Discontinuity, Concentration, Risk
Robust Evolutionary Algorithm Design for Socio-economic Simulation
Computational Economics
Genetic programming for quantitative stock selection
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
Good news: using news feeds with genetic programming to predict stock prices
EuroGP'08 Proceedings of the 11th European conference on Genetic programming
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Motivated by empirical evidence, we construct a model where heterogeneous, boundedly-rational market participants rely on a mix of technical and fundamental trading rules. The rules are applied according to a weighting scheme. Traders evaluate and update their mix of rules by genetic algorithm learning. Even for fundamental shocks with a low probability, the interaction between the traders produces a complex behavior of exchange rates. Our model simultaneously produces several stylized facts like high volatility, unit roots in the exchange rates, a fuzzy relationship between news and exchange-rate movements, cointegration between the exchange rate and its fundamental value, fat tails for returns, a declining kurtosis under time aggregation, weak evidence of mean reversion, and strong evidence of clustering in both volatility and trading volume.