The financial system performs vital functions for the economy of the whole world. The recent crisis has spurred a profound debate about the role of policy and regulations in financial markets. The debate has drawn the attention of researchers from many areas of science as well as of the civil society at large to the needs for new approaches to policy modelling. Overall, it has emerged as a prominent societal issue the need of to build a sustainable global financial system that serves the global policy goals.
It is well known that in financial markets, while contracts are beneficial to the parties involved they can also entail unforeseen (negative/positive) externalities to other parties. In particular, incentives for parties to take excessive risk as individuals lead to systemic risk for the market as a whole.
The lack of data is the immediate cause of this situation. A first step has been very recently taken in the direction of collecting systematic information for instance for OTC derivatives. In December 2012, the European Commission has adopted new technical standards, the so- called European Market Infrastructure Regulation (EMIR).
Our current understanding of what undesirable systemic effects may arise and how to cope with them is very limited. Progress in this direction is vital for the well-being
of the EU economy and requires combined efforts and competences. Furthermore, because the sustainability of the financial system is a societal issue, the input
of civic society cannot be neglected. The fact that financial instruments are complex and require very specific competences implies that it is not easy to engage civic
society directly in the discussion of the details of the policies and their effects. However, it is possible and socially desirable to increase the transparency over the interests
of the stakeholders involved in the decision making process around policies. Indeed, it is widely known that pressure exists from the financial sector on the decision making
process that should determine how to regulate the financial sector itself.
In this unit, we
- collect and make available a variety of data regarding the network structure of financial markets;
- model the financial market evolution, thereby providing to scientists, practitioners and regulators an instrument to simulate plausible scenarios;
- quantify the probability of contagion in an interbank network;
- individuate early-warning signals of upocming critical events;
- reconstruct missing information (in monopartite, bipartite and multiplex networks) with methods and models taken from statistical physics.