We present an approach ofm ulti-agent market modeling on the basis of cognitive systems with three functionality features. These features are perception, internal processing and acting. A cognitive system is structurally represented by an error correction neural network. On the mirco-level we describe agents decisions behavior by combining cognitive systems with a framework of multi-agent market modeling. By aggregating agents decisions we are able to capture the underlying market dynamics on the macro-level. As an application, we apply our approach to the DEM/USD FX-Market. Fitting real-world data, our approach is superior to more conventional forecasting techniques.
CITATION STYLE
Zimmermann, G., Neuneier, R., & Grothmann, R. (2001). Multi-agent FX-market modeling based on cognitive systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2130, pp. 767–774). Springer Verlag. https://doi.org/10.1007/3-540-44668-0_107
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