Abstract
We study the structural correlations in the Italian overnight money market over the period 1999–2010. We show that the structural correlations vary across different versions of the network. Moreover, we employ different configuration models and examine whether higher-level characteristics of the observed network can be statistically reconstructed by maximizing the entropy of a randomized ensemble of networks restricted only by the lower-order features of the observed network. We find that often many of the high order correlations in the observed network can be considered emergent from the information embedded in the degree sequence in the binary version and in both the degree and strength sequences in the weighted version. However, this information is not enough to allow the models to account for all the patterns in the observed higher order structural correlations. In particular, one of the main features of the observed network that remains unexplained is the abnormally high level of weighted clustering in the years preceding the crisis, i.e., the huge increase in various indirect exposures generated via more intensive interbank credit links.
Highlights
The interbank money market is an important means for exchanging liquidity between banks and plays a vital role in monetary policy transmission
Recalling that under the directed binary configuration model (DBCM), both out-going and in-coming degrees are enforced on average over the ensemble, we show the comparisons between the structural correlations of observed network and those obtained from that model in Figures and, Figures and, and Figures and
Instead of preserving the observed degree sequence(s) as in the Binary Configure Models (i.e., Undirected Binary Configuration Model (UBCM), Directed Binary Configuration Model (DBCM)), first, we employ the weighted configuration model preserving the observed strength sequence(s) and examine whether the chosen null models can replicate the structural correlations in the observed weighted network
Summary
The interbank money market is an important means for exchanging liquidity between banks and plays a vital role in monetary policy transmission. While some of the network properties of the e-MID market have been previously studied (see, for example, [13,18,19,20,21,22,23,24]), what is novel in our paper is that: (i) we provide a more comprehensive analysis of the structural correlations in all versions of the network, and employ both local as well as global measures for analyzing such patterns; (ii) we employ configuration models to investigate whether the intrinsic node heterogeneity represented by the degree sequence (in the binary network) and/or strength sequence (in the weighted network) can explain higher order structural correlations observed in the system; (iii) we utilize the so called Directed Enhanced Configuration Model as a null model for the directed weighted version of the network, which makes use of the available information on the direction of the edges in the network. At the end of this paper, the Appendix A provides additional details concerning the measures of structural correlations, and the Appendix B provides the distributions of expected link probabilities and weights under the different configuration models
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