Arbeitspapier

Structural correlations in the Italian overnight money market: An analysis based on network configuration models

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.

Language
Englisch

Bibliographic citation
Series: Economics Working Paper ; No. 2017-02

Classification
Wirtschaft
Banks; Depository Institutions; Micro Finance Institutions; Mortgages
Financial Crises
Monetary Systems; Standards; Regimes; Government and the Monetary System; Payment Systems
Subject
Interbank Network
Structural Correlations
Clustering Coefficients
Configuration Models
Network Reconstruction

Event
Geistige Schöpfung
(who)
Luu, Duc Thi
Lux, Thomas
Yanovski, Boyan
Event
Veröffentlichung
(who)
Kiel University, Department of Economics
(where)
Kiel
(when)
2017

Handle
Last update
28.02.1970, 12:00 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Luu, Duc Thi
  • Lux, Thomas
  • Yanovski, Boyan
  • Kiel University, Department of Economics

Time of origin

  • 2017

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