Bootstrapping topology and systemic risk of complex networks using the fitness model
Information about 10% of the links in a complex network is sufficient to reconstruct its main features and resilience with the fitness model.
Journal of Statistical Physics 151, 720 (2013)
N. Musmeci, S. Battiston, G. Caldarelli, M. Puliga, A. Gabrielli
















We present a novel method to reconstruct complex network from partial information. We assume to know the links only for a subset of the nodes and to know some non-topological quantity (fitness) characterising every node. The missing links are generated on the basis of the latter quantity according to a fitness model calibrated on the subset of nodes for which links are known. We measure the quality of the reconstruction of several topological properties, such as the network density and the degree distribution as a function of the size of the initial subset of nodes. Moreover, we also study the resilience of the network to distress propagation. We first test the method on ensembles of synthetic networks generated with the Exponential Random Graph model which allows to apply common tools from statistical mechanics. We then test it on the empirical case of the World Trade Web. In both cases, we find that a subset of 10 % of nodes is enough to reconstruct the main features of the network along with its resilience with an error of 5%.
More in Systemic risk
Modelling financial systemic risk
Complex networks model the links between financial institutions and how these channels can transition from diversifying to propagating risk.
Default cascades in networks
The optimal architecture of a financial system is only dependent on its topology when the market is illiquid, and no topology is always superior.
Non-linear distress propagation
Non-linear models of distress propagation in financial networks characterise key regimes where shocks are either amplified or suppressed.
Cascades in flow networks
Coupled distribution grids are more vulnerable to a cascading systemic failure but they have larger safe regions within their networks.
Immunisation of systemic risk
Targeted immunisation policies limit distress propagation and prevent system-wide crises in financial networks according to sandpile models.
The interbank network
The large-scale structure of the interbank network changes drastically in times of crisis due to the effect of measures from central banks.
Interbank controllability
Complex networks detect the driver institutions of an interbank market and ascertain that intervention policies should be time-scale dependent.
Fragility of the interbank network
The speed of a financial crisis outbreak sets the maximum delay before intervention by central authorities is no longer effective.
The price of complexity
Increasing the complexity of the network of contracts between financial institutions decreases the accuracy of estimating systemic risk.
DebtRank and shock propagation
A dynamical microscopic theory of instability for financial networks reformulates the DebtRank algorithm in terms of basic accounting principles.