Network topology and the behavior of socially-embedded financial markets

Olivier Brandouy () and Philippe Mathieu ()
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Olivier Brandouy: GREThA - Groupe de Recherche en Economie Théorique et Appliquée - UB - Université de Bordeaux - CNRS - Centre National de la Recherche Scientifique, UB - Université de Bordeaux
Philippe Mathieu: SMAC - Systèmes Multi-Agents et Comportements - CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 - Centrale Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 - Centrale Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique, Université de Lille

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Abstract: We study the impact of the network topology on various market parameters (volatility, liquidity and efficiency) when three populations or artificial trades interact (Noise, Informed and Social Traders). We show, using an agent-based set of simulations that choosing a Regular, a Erdos-Renyi or a scale free network and locating on each vertex one Noise, Informed or Social Trader, substantially modifies the dynamics of the market. The overall level of volatility, the liquidity and the resulting efficiency are impacted by this initial choice in various ways which also depends upon the proportion of Informed vs. Noise Traders.

Keywords: Social networks comparison; Multi-agent Systems; Financial markets microstructure (search for similar items in EconPapers)
Date: 2018-06-20
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Published in Workshop on Agent-Based Artificial Markets Computational Economics (ABAM), Jun 2018, Toledo, Spain. pp.93-104

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01742101

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