Cross-border interbank networks, banking risk and contagion

Abstract

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Networks in Risk Spillovers: A Multivariate GARCH Perspective

“…In this enterprise, we take inspiration from a recent strand of spatial econometrics literature that includes finance-based weight matrices in their analysis (Keiler and Eder (2013), Blasques et al (2016), Tonzer (2015), and Billio et al (2017)), and starts to introduce the network terminology in the discussion. However, building on Caporin and Paruolo (2015) differentiates us from the latter papers.…”

“…Previous applications of spatial methods to financial markets average these time-varying relationships, reducing to a static framework (see, as an example, Tonzer (2015)). This contribution is not completely new; however, we are the first to embed the time-varying nature of financial proximity within a conditional covariance model, going beyond the static weight matrix used in Caporin and Paruolo (2015).…”

“…The second ingredient is our consideration of the weight matrix as a directed network. Directedness is not present in classical approaches, but is already considered in Billio et al (2017);Tonzer (2015) and Blasques et al (2016).…”

“…The intersection and interaction of different research fields, such as network science, spatial econometrics, economics, and finance, give rise to new developments and tools. In particular, one of the most advanced strands of the spatial econometrics literature (see Keiler and Eder (2013); Blasques et al (2016); Caporin and Paruolo (2015); Tonzer (2015); Billio et al (2017)) focuses on statistical, economic, and financial relationships. Our work belongs to this strand of the literature and aims at building a bridge between contagion, volatility spillover, and networks.…”

“…This is particularly important in applications since, as already remarked, we are not only able to obtain the statistical significance of a given channel, as in Tonzer (2015), but also to distinguish the importance of different nodes by using diagonal matrix parameters. Moreover, the use of directed networks (i.e., asymmetric proximity) allows us to weight the transmission channel according to their direction, and we recover information on the statistically relevant channels of contagion, resulting in a better understanding of risk circulation.…”