Abstract
We present an approach of multi-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.
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Zimmermann, G., Neuneier, R., Grothmann, R. (2001). Multi-agent FX-Market Modeling Based on Cognitive Systems. In: Dorffner, G., Bischof, H., Hornik, K. (eds) Artificial Neural Networks — ICANN 2001. ICANN 2001. Lecture Notes in Computer Science, vol 2130. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44668-0_107
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DOI: https://doi.org/10.1007/3-540-44668-0_107
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