By Philippe Mathieu, Bruno Beaufils, Olivier Brandouy
Agent-based Computational Economics (ACE) is a brand new self-discipline of economics, mostly grounded on suggestions like evolution, auto-organisation and emergence: it intensively makes use of desktop simulations in addition to man made intelligence, usually in keeping with multi-agents platforms. the aim of this ebook is to offer an up-to date view of the clinical creation within the fields of Agent-based Computational Economics (mainly in industry Finance and video game Theory). in line with communications given at AE'2005 (Lille, USTL, France), this booklet deals a large landscape of contemporary advances in ACE (both theoretical and methodological) that might curiosity teachers in addition to practitioners.
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Additional info for Artificial Economics: Agent-Based Methods in Finance, Game Theory and Their Applications
In those conditions, we observed that after a transition period, characterised by high volumes, during which assets were heavily reallocated between agents, the price kept fluctuating around a steady state equilibrium price. This price, emergingfi*omthe interactions between heterogeneous, relative risk aversion agents, was generally different from the fundamental value we could have expected from rational agents with homogeneous preferences. 4 Conclusion The rapidly growing field of Agent-based Computational Finance comes naturally as a complementary approach to the other Finance subfields: Behavioural Finance, Laboratory experiments.
1 Experimental Setup Our experiment features a continuous double-auction implemented on the NatLab simulation platform. Every participant received extensive support from a computer scientist to implement his/her avatar in C++ on the platform. NatLab platform The NatLab has the capability to simulate in great detail the continuum time asynchronous real world . Bilateral and multilateral communication between agents outside and in parallel with the market is made possible by NatLab. However, given that this experiment focuses mainly on the participants behaviour, we kept the market mechanism (the rules of the game) as simple as possible, while retaining the concept of continuous double-auction, essential to understand the price formation dynamics.
34 Gilles Daniel et al. Avatars We organise our experiment as a competition between participants through the intermediary of their avatars. Avatars generate, by assigning values to their parameters, families of agents that act as independent (but possibly interacting) individuals in the market. The subjects' aim in each run is to generate a family of artificial agents that perform well against other families throughout the simulation run. A typical simulation run is exhibited in Fig. 4. Families were compared by their average wealth, but an average utility (given some utility function) or a certain bonus for minimising risk could be used in the future.