Three-state opinion dynamics for financial markets on complex networks

This work investigates the effects of fundamental complex network structures on the collective behavior of a three-state opinion formation model in economic systems. Our model considers two distinct types of investors in financial markets: noise traders and fundamentalists. Financial states evolve via probabilistic dynamics that include economic strategies with local and global influences. The local majoritarian opinion drives noise traders’ market behavior, while the market index influences the financial decisions of fundamentalist agents. We introduce a level of market anxiety q present in the decision-making process that influences financial actions. In our investigation, nodes of a complex network represent market agents, whereas the links represent their financial interactions. We investigate the stochastic dynamics of the model under the influence of hub agents, clustering, small-world effects and connectivity randomness using three distinct network topologies: scale-free, small-world and random networks. Our model mirrors various traits observed in real-world financial return series, such as heavy-tailed return distributions, volatility clustering, and short-term memory correlation of returns. The histograms of returns are fitted by coupled exponential distributions, quantitatively revealing transitions from a leptokurtic to a mesokurtic regime under specific economic heterogeneity. We show that the modeled market dynamics depend mainly on the average agent connectivity, anxiety level, and market composition rather than on other specific fundamental structures of network topology.