Statistically validated network of portfolio overlaps and systemic risk

Abstract

Common asset holding by financial institutions (portfolio overlap) is nowadays regarded as an important channel for financial contagion with the potential to trigger fire sales and severe losses at the systemic level. We propose a method to assess the statistical significance of the overlap between heterogeneously diversified portfolios, which we use to build a validated network of financial institutions where links indicate potential contagion channels. The method is implemented on a historical database of institutional holdings ranging from 1999 to the end of 2013, but can be applied to any bipartite network. We find that the proportion of validated links (i.e. of significant overlaps) increased steadily before the 2007–2008 financial crisis and reached a maximum when the crisis occurred. We argue that the nature of this measure implies that systemic risk from fire sales liquidation was maximal at that time. After a sharp drop in 2008, systemic risk resumed its growth in 2009, with a notable acceleration in 2013. We finally show that market trends tend to be amplified in the portfolios identified by the algorithm, such that it is possible to have an informative signal about institutions that are about to suffer (enjoy) the most significant losses (gains).

Core of communities in bipartite networks

“…Several studies have recently selected a subset of links of a network on the basis of a statistical test considering a well defined null hypothesis [18,[20][21][22][23]. These subsets have been called statistically validated networks [18].…”

Inferring monopartite projections of bipartite networks: an entropy-based approach

“…A different class of methods, on the other hand, focuses on projecting a statistically validated network by estimating the tendency of any two nodes belonging to the same layer to share a given portion of neighbors. All approaches define a similarity measure which either ranges between 0 and 1 [10,11] or follows a probability distribution on which a p-value can be computed [12][13][14]. While in the first case the application of an arbitrary threshold is still unavoidable, in the second case prescriptions rooted in traditional statistics can be applied.…”

The Application of Macroprudential Capital Requirements in Managing Systemic Risk

“…One is the network of banks investing in similar types of assets, in which one bank failure can lead to a fall in the price of its assets and then affect the solvency of other banks that hold the same assets [12,13]. The other is the risk of contagion in the interbank market, which concerns the liquidity risk of contagion at a form of interlocking exposure; such exposure is very short term, mainly overnight.…”