The Great Financial Crisis has shown that economists had serious weaknesses in their understanding of financial stability. This misunderstanding is mainly related to systemic risk, that is the risk of collapse of the entire financial market rather than of a single institution.
The mechanisms that lies behind this kind of risk is generated from the tangled and complex nature of balance sheets linkages, that through what is called emergent behavior (i.e. when the aggregate, the whole, is not simply the sum of its parts), transforms behaviors that are probably optimal at the individual level to not-optimal ones in the aggregate.
Financial networks, if having a high degree of systemic risk, can thus amplify shocks rather than absorbing them, even if all the agents are performing individually optimal risk-management decisions. An example of this situation is the failure of Lehman Brothers, where the market totally collapsed for a failure of one institution, that is one node in the network.
These events increased the interest in network theory and agent-based model, methodologies that can effectively represent what we have observed. Several models describe how the shape of the networks affects financial stability, how shocks propagate through these networks and which kind of shocks has more effect on them. These results have important consequences from a policy perspective: they could be valuable tools for the decision making of policy makers.
My research will thus follow and try to improve this literature, focusing on how the financial network endogenously changes in shape and on how it is possible to calibrate them to real world interconnectedness data.
As previously said, interest in these topics has grown only recently, after the financial crisis. Thus, there are a lot of possibility for extending the literature.
The core of this research, the financial network, is being treated for now in an exogenous way. From a theoretical point of view, an important advancement would be the endogenous formations of such networks, possibly using approaches different from the standard general equilibrium (Elliott, Golub, & Jackson, 2014).
This need for research has also been underlined by (Acemoglu, Ozdaglar, & Tahbaz-Salehi, 2015), with a stress on the efficiency and policy implications of the various network structures. A further extension that they suggest is the introduction of more variety in the type of interactions, including more financial instruments and more possibilities for indirect contagion. Finally, they suggest that the type of actors interacting in the network should be broadened, including for example some non-bank financial institutions (that have played a very relevant role in the last financial crisis).
While, from a more practical view, would be of incredible usefulness to calibrate the network used in the simulation to real-world data, even if right now there are strong limits to the collection of this information (Gai, Haldane, & Kapadia, 2011).
My research will thus focus on these open questions, trying to address them.
References
Acemoglu, D., Ozdaglar, A., & Tahbaz-Salehi, A. (2015). Systemic Risk and Stability in Financial Networks. American Economic Review, 105(2), 564¿608. https://doi.org/10.1257/aer.20130456
Elliott, M., Golub, B., & Jackson, M. (2014). Financial Networks and Contagion (January 2014). In American Economic Review (Vol. 104). https://doi.org/10.2139/ssrn.2175056
Gai, P., Haldane, A., & Kapadia, S. (2011). Complexity, concentration and contagion. Journal of Monetary Economics, 58(5), 453¿470. https://doi.org/10.1016/j.jmoneco.2011.05.005