Methods for Reconstructing Interbank Networks from Limited Information: A Comparison
In this chapter, we review and compare some methods for the reconstruction of an interbank network from limited information. By exploiting the theory of complex networks and some ideas from statistical physics, we mainly focus on three different methods based on the maximum entropy principle, the relative entropy minimization, and the fitness model. We apply our analysis to the credit network of electronic Market for Interbank Deposit (e-MID) in 2011. In comparing the goodness of fit of the proposed methods, we look at the topological network properties and how reliably each method reproduces the real-world network.
- Barucca, P. and Lillo, F. (2015). The organization of the interbank network and how ecb unconventional measures affected the e-mid overnight market. http://arxiv.org/abs/1511.08068.
- Battiston, S., Puliga, M., Kaushik, R., Tasca, P., and Caldarelli, G. (2012). Debtrank: Too central to fail? financial networks, the fed and systemic risk. Scientific reports, 2.Google Scholar
- Blien, U. and Graef, F. (1991). Entropy optimization in empirical economic research-the estimation of tables from incomplete information. JAHRBUCHER FUR NATIONALOKONOMIE UND STATISTIK, 208(4):399–413.Google Scholar
- Cimini, G., Squartini, T., Garlaschelli, D., and Gabrielli, A. (2015b). Systemic risk analysis on reconstructed economic and financial networks. Scientific reports, 5.Google Scholar
- Cont, R., Moussa, A., et al. (2010). Network structure and systemic risk in banking systems. Edson Bastos e, Network Structure and Systemic Risk in Banking Systems (December 1, 2010).Google Scholar
- Di Gangi, D., Lillo, F., and Pirino, D. (2015). Assessing systemic risk due to fire sales spillover through maximum entropy network reconstruction. Available at SSRN 2639178.Google Scholar
- Gai, P. and Kapadia, S. (2010). Contagion in financial networks. In Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, page rspa20090410. The Royal Society.Google Scholar
- Geyer, C. J. and Thompson, E. A. (1992). Constrained monte carlo maximum likelihood for dependent data. Journal of the Royal Statistical Society. Series B (Methodological), pages 657–699.Google Scholar
- Sheldon, G., Maurer, M., et al. (1998). Interbank lending and systemic risk: an empirical analysis for switzerland. REVUE SUISSE D ECONOMIE POLITIQUE ET DE STATISTIQUE, 134:685–704.Google Scholar
- Silvestri, L. and Cont, R. (2015). Essays on systemic risk, financial networks and macro-prudential regulation. PhD Thesis.Google Scholar
- Snijders, T. A. (2002). Markov chain monte carlo estimation of exponential random graph models. Journal of Social Structure, 3(2):1–40.Google Scholar
- Wells, S. J. (2004). Financial interlinkages in the united kingdom’s interbank market and the risk of contagion.Google Scholar