Opinion dynamics in financial markets via random networks

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 Erdos-Renyi 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.

Automated summary

We investigate financial market dynamics using a heterogeneous agent-based opinion formation model. The model organizes individuals in the market based on their trading strategies and considers the interactions between noise traders and fundamentalists. Results show that the model exhibits key features of real-world markets, such as fat-tailed distribution of logarithmic returns, clustered volatility, and long-term return correlation.