Do Information Contagion and Business Model Similarities Explain Bank Credit Risk Commonalities?

Abstract

This paper revisits the credit spread puzzle in bank CDS spreads from the perspective of information contagion. The puzzle, first detected in corporate bonds, consists of two stylized facts: Structural determinants of credit risk not only have low explanatory power but also fail to capture common factors in the residuals (Collin-Dufresne et al., 2001). For the case of banks, we hypothesize that the puzzle exists because of omitted network effects. We therefore extend the structural models to account for information spillovers based on bank business model similarities. To capture this channel, we propose and construct a new intuitive measure for portfolio overlap using the complete asset holdings of the largest banks in the Eurozone. Incorporating the network information into the structural model for bank credit spreads increases explanatory power and removes a systemic common factor as well as a North-South common factor from the residuals. Furthermore, neglecting the network likely overstates the importance of structural determinants.

A multilevel analysis to systemic exposure: insights from local and system-wide information

“…Our final sample consists of 46 financial institutions embedding banks, brokerdealers, insurance and real-estate companies listed in the Standard & Poors 500 index. Note that such a network is similar in size or larger than most related studies on market-based financial spillovers such as [17], [18] or [19].…”

Networking the Yield Curve: Implications for Monetary Policy

“…Yet these papers work under the assumption of sparseness of the weights matrix and do not consider timevarying spillovers. On the other hand, for example, Blasques et al (2016), Catania and Billé (2017), and Wang et al (2018) model time-varying networks in a generalized autoregressive score (GAS) framework, yet they assume the weights to be pre-determined. We expand on these papers and extend the GAS model to allow for an endogenous, potentially asymmetric weights matrix.…”