Volatility polarization of non-specialized investors' heterogeneous activity

Financial markets provide an ideal frame for studying decision making in crowded environments. Both the amount and accuracy of the data allows to apply tools and concepts coming from physics that studies collective and emergent phenomena or self-organised and highly heterogeneous systems. We analyse the activity of 29,930 non-expert individuals that represent a small portion of the whole market trading volume. The very heterogeneous activity of individuals obeys a Zipf's law, while synchronization network properties unveil a community structure. We thus correlate individual activity with the most eminent macroscopic signal in financial markets, that is volatility, and quantify how individuals are clearly polarized by volatility. The assortativity by attributes of our synchronization networks also indicates that individuals look at the volatility rather than imitate directly each other thus providing an interesting interpretation of herding phenomena in human activity. The results can also improve agent-based models since they provide direct estimation of the agent's parameters.