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Thesis

French

ID: <

10670/1.8aqkqq

>

Where these data come from
Dynamics and control of financial market with a multi-agent system approach

Abstract

This thesis suggests reflection in studying financial markets through complex systems prism.First, an original mathematic description for describing agents' decision-making process in case of problems affecting by both individual and collective behavior is introduced. The proposed method is particularly applicable when studied system is characterized by non-linear, path dependent and self-organizing interactions. An application to financial markets is proposed by designing a multi¬agent system based on the proposed formalization.In this application, we propose to implement a computational agent-based financial market in which the system is described in both a microscopie and macroscopic levels are proposed. The agents' decision-making process is based on fuzzy logic rules and the price dynamic is purely deten-ninistic according to the basis matching rules of a central order book as in NYSE-Euronext-Paris. We show that, while putting most parameters under evolutionary control, the computational agent- based system is able to replicate several stylized facts of financial time series (distributions of stocks returns showing a heavy tau l with positive excess kurtosis and volatility clustering phenomenon).Thereafter, with numerical simulations we propose to study three system's properties: self-organization, resilience and robustness. First a method is introduced to quantify the degree of selforganization which ernerges in the system and shows that the capacity of self-organization is maximized when the agents' behaviors are heterogeneous. Secondly, we propose to study the system's response when market shock is simulated. in both cases, numerical results are presentedI and analyzed, showing how the global market behavior emerges from specific individual behavior interactions.Our results notably show that the emergence of collective herding behavior when market shock occurs leads to a temporary disruption on the system self-organization. Finaily, numerical simulations highlight that our artificial financial market can be able to absorb strong mono-shock but be lead to the rupture by low but repeated perturbations.

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