How connected is the global sovereign credit risk network?

By Gorkem Bostanci, K. Yilmaz. Journal of Banking & Finance, 2020

171 citations recorded by the source corpus.

We apply the Diebold-Yilmaz connectedness index methodology on sovereign credit default swaps (SCDSs) to estimate the network structure of global sovereign credit risk. In particular, using the elastic net estimation method, we separately estimate networks of daily SCDS returns and volatilities for 38 countries between 2009 and 2014. Our results reveal striking differences between the network structures of returns and volatilities. In SCDS return networks, developing and developed countries stand apart in two big clusters. In the case of the SCDS volatility networks, however, we observe regional clusters among emerging market countries along with the developed-country cluster. We also show that global factors are more important than domestic factors in the determination of SCDS returns and volatilities. Finally, emerging market countries are the key generators of connectedness of sovereign credit risk shocks while severely problematic countries as well as developed countries play relatively smaller roles.

Subfields: Finance, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/0b9d3aa7e95f686465b7932a686c827344db38dc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Finance

In Strategy and Management

Yongcheol Shin

Citations in the corpus

Quantile Connectedness: Modeling Tail Behavior in the Topology of Financial Networks (2022, background): “…(e.g. Baruńık, Kočenda and Vácha, 2016; Greenwood-Nimmo, Nguyen and Rafferty, 2016), systemically important financial institutions (e.g. Demirer, Diebold, Liu and Yilmaz, 2018) and sovereign and corporate credit spreads (e.g. Greenwood-Nimmo, Huang and Nguyen, 2019; Bostanci and Yilmaz, 2020).”