Opinion dynamics in financial markets via random networks

Mateus F. B. Granha, André L. M. Vilela (), Chao Wang (), Kenric P. Nelson and H. Eugene Stanley
Additional contact information
Mateus F. B. Granha: a Física de Materiais, Escola Politécnica de Pernambuco, Universidade de Pernambuco , Recife , PE 50720-001 , Brazil
André L. M. Vilela: b Center for Polymer Studies, Department of Physics, Boston University , Boston , MA 02215
Chao Wang: c College of Economics and Management, Beijing University of Technology , Beijing 100124 , China
Kenric P. Nelson: d Photrek LLC , Watertown , MA 02472
H. Eugene Stanley: b Center for Polymer Studies, Department of Physics, Boston University , Boston , MA 02215

Proceedings of the National Academy of Sciences, 2022, vol. 119, issue 49, e2201573119

Abstract:

We investigate financial market dynamics by introducing a heterogeneous agent-based opinion formation model. In this work, we organize individuals in a financial market according to their trading strategy, namely, whether they are noise traders or fundamentalists. The opinion of a local majority compels the market exchanging behavior of noise traders, whereas the global behavior of the market influences the decisions of fundamentalist agents. We introduce a noise parameter, q , to represent the level of anxiety and perceived uncertainty regarding market behavior, enabling the possibility of adrift financial action. We place individuals as nodes in an Erdös-Rényi random graph, where the links represent their social interactions. At any given time, individuals assume one of two possible opinion states ±1 regarding buying or selling an asset. The model exhibits fundamental qualitative and quantitative real-world market features such as the distribution of logarithmic returns with fat tails, clustered volatility, and the long-term correlation of returns. We use Student’s t distributions to fit the histograms of logarithmic returns, showing a gradual shift from a leptokurtic to a mesokurtic regime depending on the fraction of fundamentalist agents. Furthermore, we compare our results with those concerning the distribution of the logarithmic returns of several real-world financial indices.

Keywords: econophysics; sociophysics; Monte Carlo simulation; phase transitions; complex networks (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:nas:journl:v:119:y:2022:p:e2201573119

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