Abstract
We propose an intuitive toy model of a financial market where investors are represented by hungry sharks. Each shark learns the best strategy through a trial and error procedure calibrated to human characteristics. The mix of rewards for eating or not can create a large array of scenarios that can be used to observe the emergence of equilibrium from simple to more realistic situations. Using an agent-based model we create an environment where sharks learn and try to optimize their payoffs. Our preliminary results show that sharks,like investors, can learn to coordinate and generate a equilibrium under rational expectations. We also find cases where equilibrium cannot be found and the situation becomes a minority-type game.
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Stanciu-Viziteu, L.D. (2012). The shark game: equilibrium with bounded rationality. In: Teglio, A., Alfarano, S., Camacho-Cuena, E., Ginés-Vilar, M. (eds) Managing Market Complexity. Lecture Notes in Economics and Mathematical Systems, vol 662. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31301-1_9
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DOI: https://doi.org/10.1007/978-3-642-31301-1_9
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