The modern science of networks has brought significant advances to our understanding of
complex systems. One of the most relevant features of graphs representing real systems is …

In recent years there has been a shift in focus from the study of local, mostly task-related
activation to the exploration of the organization and functioning of large-scale structural and …

Since inflation of commodities is becoming more and more severe recently caused by many
macro events, such as COVID-19 and Russian-Ukrainian conflict, systemic risk of commodity …

We introduce a technique to filter out complex data sets by extracting a subgraph of
representative links. Such a filtering can be tuned up to any desired level by controlling the …

The time dependence of the recently introduced minimum spanning tree description of
correlations between stocks, called the “asset tree” has been studied in order to reflect the …

Modularity is a fundamental concept in systems neuroscience, referring to the formation of
local cliques or modules of densely intra-connected nodes that are sparsely inter-connected …

This article and the companion paper aim at reviewing recent empirical and theoretical
developments usually grouped under the term Econophysics. Since the name was coined in …

We review the recent approach of correlation based networks of financial equities. We
investigate portfolio of stocks at different time horizons, financial indices and volatility time …

We live in a computerized and networked society where many of our actions leave a digital
trace and affect other people's actions. This has lead to the emergence of a new data-driven …

Networks of companies can be constructed by using return correlations. A crucial issue in
this approach is to select the relevant correlations from the correlation matrix. In order to …