  This work investigates the effects of complex networks 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 action. 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 on three
distinct network topologies, including scale-free networks, small-world
networks and Erd{\"o}s-R\'enyi random graphs. 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 Gaussian
distributions, quantitatively revealing transitions from a leptokurtic to a
mesokurtic regime under specific economic heterogeneity. We show that the
market dynamics depend mainly on the average agent connectivity, anxiety level,
and market composition rather than on specific features of network topology.
