Systemic risk assessment through high order clustering coefficient

Abstract

In this article we propose a novel measure of systemic risk in the context of financial networks.To this aim, we provide a definition of systemic risk which is based on the structure, developed at different levels, of clustered neighbours around the nodes of the network. The proposed measure incorporates the generalized concept of clustering coefficient of order l of a node i introduced in [10]. Its properties are also explored in terms of systemic risk assessment. Empirical experiments on the time-varying global banking network show the effectiveness of the presented systemic risk measure and provide insights on how systemic risk has changed over the last years, also in the light of the recent financial crisis and the subsequent more stringent regulation for globally systemically important banks.

Modeling Overlapped Mutual Funds’ Portfolios: A Bipartite Network Approach

“…These results are interesting because the equity portfolios we analyzed in this study fall within the characteristic of overlapped portfolios, confirming the existence of a channel of contagion generated by the aggregate investment behavior of the entities belonging to the network. Similar results are showed by the network literature that study the effects of the interconnectedness of financial institutions and the propagation of shocks over the systemic risk of the financial market [40,41,45]. From a policy and regulator point of view, this evidence highlights that improving the knowledge of overlapping portfolios in emerging markets, is a fundamental element to a better understanding of the risks and magnitudes of financial and economic contagions with respect to the likelihood of their occurrence and extension, and their relation to the number and density of the connections within the financial system.…”

“…The network literature states that, in context of financial stress, the interconnectedness among financial institutions play a key role in terms of the systemic risk of the market. In these situations, a shock on a node of the system could trigger a collapse of the entire financial network [40]. Usually these shocks have an exogenous origin.…”

A new measure of the resilience for networks of funds with applications to socially responsible investments

“…In particular, we employ a particular version of the clustering coefficient of the network (see [23]) to assess the presence of large (small) deviations of networks structure from absence to presence of shocks -i.e., weak (strong) resilience measure. In so doing, we are in line with a wide strand of literature employing the clustering coefficient for dealing with resilience measures (see, e.g., [24][25][26][27]).…”

Financial interbanking networks resilience under shocks propagation

“…Bongini et al 2018 ; Cerqueti et al. 2020 ; Cinelli et al 2021 ; Demir and Onder 2019 ; Giudici and Spelta 2016 ; Minoiu and Reyes 2013 ; Minoiu et al 2015 ). The BIS is owned by 62 central banks covering about 95% of the world’s GDP (BIS database www.bis.org ).…”

“…Following previous contributions in the quantitative finance literature, we have retrieved the empirical quarterly data from the Bank for International Settlements (BIS) database (see e.g. Bongini et al 2018;Cerqueti et al 2020;Cinelli et al 2021;Demir and Onder 2019;Giudici and Spelta 2016;Minoiu and Reyes 2013;Minoiu et al 2015). The BIS is owned by 62 central banks covering about 95% of the world's GDP (BIS database www.bis.org).…”