This paper proposes a new methodology based on non-negative matrix factorization to detect communities and to identify central nodes in a network as well as within communities. The method is specifically designed for directed weighted networks and, consequently, it has been applied to the interbank network derived from the e-MID interbank market. In an interbank network indeed links are directed, representing flows of funds between lenders and borrowers. Besides distinguishing between Systemically Important Borrowers and Lenders, the technique complements the detection of systemically important banks, revealing the community structure of the network, that proxies the most plausible areas of contagion of institutions’ distress.
Pecora, N., Kaltwasser, P. R., Spelta, A., Discovering SIFIs in Interbank Communities, <<PLOS ONE>>, 2016; 11 (12): N/A/-N/A. [doi:10.1371/journal.pone.0167781] [http://hdl.handle.net/10807/90683]
Discovering SIFIs in Interbank Communities
Pecora, Nicolo'Primo
;Spelta, AlessandroUltimo
2016
Abstract
This paper proposes a new methodology based on non-negative matrix factorization to detect communities and to identify central nodes in a network as well as within communities. The method is specifically designed for directed weighted networks and, consequently, it has been applied to the interbank network derived from the e-MID interbank market. In an interbank network indeed links are directed, representing flows of funds between lenders and borrowers. Besides distinguishing between Systemically Important Borrowers and Lenders, the technique complements the detection of systemically important banks, revealing the community structure of the network, that proxies the most plausible areas of contagion of institutions’ distress.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.