Clustering in Dynamic Causal Networks as a Measure of Systemic Risk on the Euro Zone

Abstract

In this paper, we analyze the dynamic relationships between ten stock exchanges of the euro zone using Granger causal networks. Considering returns for which we allow the variance to follow a Markov-Switching GARCH or a Changing-Point GARCH process, we …rst show that over di¤erent periods, the topology of the network is highly unstable. In particular dynamic relationships vanish over very recent years. Then, expandingon this idea, we analyze patterns of information transmission within the network. Using rolling windows to study networks' topology in terms of information clustering, we …nd that the nodes'state changes continually.Moreover, the system exhibits periods of ‡ickering in information transmission. During these periods of ‡ickering, the system also exhibits desynchronization in the information transmission process. These periods do precede tipping points or phase transitions on the market, especially before the global …nancial crisis, and can thus be used as early warnings. To our knowledge, this is the …rst time that ‡ickering in information transmission

Directed clustering in weighted networks: A new perspective

“…However, our aim is to focus on clustering coefficients. It is noteworthy that several works, contributing to the debate around systemic risk, showed (see [7], [18] and [29]) that the directed clustering coefficient could provide meaningful insights in this context. In particular, in [29] the authors argue that higher clustering of the "in" type may reflect higher systemic risk because failure of the borrowing node in an "in" triangle can trigger simultaneous non-repayments to the lending nodes, and this, in turn, can make them unable to honor their own obligations.…”

Global financial interconnectedness: a non-linear assessment of the uncertainty channel

“…It means that interconnections among assets at a given date are not necessarily the same at another one. Against this background, Billio et al (2016) have recently proposed a statistical approach based on Granger causality and MS-GARCH to deal with such dynamic networks. Treating network as information diffusion, they show that some structures inherent to the system, such as the number of connections among stock exchanges and their associated strengths, are regime-dependent.…”

“…Indeed unlike VAR setting, Granger causal approach is directional but exclusively pairwise and unweighted, tests zero versus non-zero coefficients with somewhat arbitrary significance levels and does not track the magnitude of non-zero coefficients. 12 On the other hand, it is well known that variance decomposition and impulse response analysis may suffer from identifying assumptions inherent to VAR setting. However, this restriction can be partially mitigated by careful robustness checks as we do in the empirical part of the paper.…”

One Scheme Fits All: A Central Fiscal Capacity for the EMU Targeting Eurozone, National and Regional Shocks

“…Other studies employ Granger causality tests in means to construct causality networks among stock indices (Lee and Yang (2014), Billio et al (2016)), sovereign bond yields (Caporin et al (2018)) or multi-partite networks, e.g. combining stocks and sovereign bond yields (Corsi et al (2018)).…”