Complex networks and complexity finance

Session chair:

Małgorzata Snarska –



Complex systems surround us. We are complex ourselves. Social phenomena like the emergence of communication and cooperation, a build-up of hierarchies and organizations, opinion formation, the emergence of political systems, and the structure and dynamics of financial markets are iconic examples of real-world complexity. Therefore, their better understanding, description, and prediction of their future behaviors is an exciting scientific challenge. Today’s technology development level allows for an empirical analysis of large-scale and complex dynamical networks generated by nature. It enables the construction and verification of more sophisticated models. One of the tools that contribute to a complete description of complex phenomena is the language of complex networks developed for more than two decades.

This particular track covers various complexity-related topics and methods in the following fields: wealth distributions and inequalities ineconomics, financial markets (e.g., cryptocurrencies, energy markets), time series analysis, graphical models.  The track is related to quantitative analysis of complex network phenomena with a focus on economics and finance.


Submissions related to heterogeneous interacting agents, complex networks, and non-extensive entropy with applications in financial markets are especially welcomed. We also highly invite original theoretical works related to graphical models and comprehensive review papers combining statistical physics with economy and finance. Papers with applications of complex networks formalism to explain financial and economic phenomena are also encouraged.