Opinion dynamics in financial markets via random networks

Author:

Granha Mateus F. B.1ORCID,Vilela André L. M.12ORCID,Wang Chao3ORCID,Nelson Kenric P.4ORCID,Stanley H. Eugene2ORCID

Affiliation:

1. Física de Materiais, Escola Politécnica de Pernambuco, Universidade de Pernambuco, Recife, PE 50720-001, Brazil

2. Center for Polymer Studies, Department of Physics, Boston University, Boston, MA 02215

3. College of Economics and Management, Beijing University of Technology, Beijing 100124, China

4. Photrek LLC, Watertown, MA 02472

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.

Funder

Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco

National Natural Science Foundation of China

National Science Foundation

DOD | Defense Threat Reduction Agency

DOE | Idaho Operations Office, U.S. Department of Energy

Publisher

Proceedings of the National Academy of Sciences

Subject

Multidisciplinary

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