By Philippe Mathieu, Bruno Beaufils, Olivier Brandouy
Agent-based Computational Economics (ACE) is a brand new self-discipline of economics, mostly grounded on thoughts like evolution, auto-organisation and emergence: it intensively makes use of desktop simulations in addition to synthetic intelligence, more often than not in response to multi-agents platforms. the aim of this publication is to provide an up-to date view of the medical creation within the fields of Agent-based Computational Economics (mainly in marketplace Finance and online game Theory). according to communications given at AE'2005 (Lille, USTL, France), this publication deals a large landscape of contemporary advances in ACE (both theoretical and methodological) that may curiosity lecturers in addition to practitioners.
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Additional resources for Artificial Economics: Agent-Based Methods in Finance, Game Theory and Their Applications
K agents must be parasitic on the intelligent agents to trade and to obtain profit. If all traders in the market are K agents no trade will take place. Although learning and the convergence to the Nash Equilibrium have been widely studied (Kirman ), there are few applications to the analysis of learning strategies in a CDA market (Walsh et al ). Walsh et al  found two Nash equilibria points when these three types agents (GD, K and ZIP) rival each other in a CDA market and their agents strategies are fixed by the modeller.
Bouchaud. Bubbles, crashes and intermittency in agent based market models. The European PhysicalJournal B, 31:421-537, 2003. 9. B. I. Jacobs, K. N. Levy, and H. Markowitz. Financial market simulations. Journal of Portfolio Management, 30th Anniversary, 2004. 10. G. Kim and H. Markowitz. Investment rules, margin, and market volatility. Journal of Portfolio Management, 16(l):45-52, 1989. 11. D. Kahneman and A. Tversky. Prospect theory: An analysis of decision under risk. Econometrica, 47(2):263-292, 1979.
Here the standard deviation is greater than the one observed on the complete sample. A bubble is hence characterized by a great deviation between the stock price and its fundamental value during a long time range. This typical dynamic, obtained with 75% of speculators and 25% of fundamentalists, can be found with other sets of parameters as long as speculator agents proportion is great (> 70%). In the speculative regime (when speculators compose the main part of population), we obtain a highly volatile price dynamic with bubbles and crashes.