Abstract
The recent global financial crisis has shown portfolio correlations between agents as one of the major channels of risk contagion and amplification. In this work, we analyse the structure and dynamics of the cross-correlation matrix of banks’ loan portfolios in the yearly bank-firm credit network of Japan during the period from 1980 to 2012. Using the methods of Random Matrix Theory (RMT), Principal Component Analysis and complex networks, we aim to detect non-random patterns in the empirical cross-correlations as well as to identify different states of such correlations over time. Our findings suggest that although a majority of portfolio correlations between banks in lending relations to firms are contributed by noise, the top largest eigenvalues always deviate from the random bulk explained by RMT, indicating the presence of non-random patterns governing the correlation dynamics. In particular, we show that this dynamics is mainly driven by a global common factor and a couple of “groups” factors. Furthermore, different states in the credit market can be identified based on the evolution of eigenvalues and associated eigenvectors. For example, during the asset price bubble period in Japan from 1986 to 1991, we find that banks’ loan portfolios tend to be more correlated, showing a significant increase in the level of systemic risk in the credit market. In addition, building Planar Maximally Filtered Graphs from the correlations of different eigenmodes, notably, we observe that the local interaction structure between banks changes in different periods. Typically, when the dominance of a group of banks in one period gradually vanishes, the credit market starts to build-up a different structure in the next period in which another group of banks will become the main actors in the backbone of the cross-correlations.
Highlights
Over the last few years, catastrophic cascade of failures in interdependent systems has received a remarkable attention in network science
Note that in the present work we focus on loan portfolio correlations between banks, we summarize the main results for loan portfolio overlaps and similarities in the ‘‘Appendix’’
We have examined the structure and the dynamics of the correlation matrices for the banks’ loan portfolios in a large data set of the bank-firm credit network of Japan during the period from 1980 to 2012
Summary
Over the last few years, catastrophic cascade of failures in interdependent systems has received a remarkable attention in network science Findings in this line of research show that the robustness of a system crucially depends on both its internal structure as well as its pattern of relations to other interdependent ones Since banks can be indirectly linked through a set of joint exposures to firms (i.e. due to loan portfolio overlaps), the distress originating from a group of banks or firms can be propagated through the whole system. For these reasons, a number of empirical studies have been devoted to uncovering the complexity of the topological structure of bank-firm credit markets world-wide A number of empirical studies have been devoted to uncovering the complexity of the topological structure of bank-firm credit markets world-wide (e.g. Fujiwara et al 2009; De Masi et al 2011; De Masi and Gallegati 2012; Fricke 2016; Marotta et al 2015, 2016; Fricke and Roukny 2020; Luu and Lux 2018, 2019; Lux 2020)
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