Network topology and the behavior of socially-embedded financial markets

Olivier Brandouy (1, 2) , Philippe Mathieu (3, 4, 5)

1 GREThA - Groupe de Recherche en Economie Théorique et Appliquée
2 UB - Université de Bordeaux
3 SMAC - Systèmes Multi-Agents et Comportements
4 CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
5 Université de Lille

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.

Mots clés: Social networks comparison; Multi-agent Systems; Financial markets microstructure

Domaines: Système multi-agents [cs.MA]; Modélisation et simulation; Intelligence artificielle [cs.AI]; Microstructure des marchés [q-fin.TR]; Finance [q-fin.GN]

Olivier Brandouy, Philippe Mathieu. Network topology and the behavior of socially-embedded financial markets. Workshop on Agent-Based Artificial Markets Computational Economics (ABAM), Jun 2018, Toledo, Spain. pp.93-104. ⟨hal-01742101⟩