Dynamic Credit Default Swaps Curves in a Network Topology

SFB 649 Discussion Paper 2016-059

47 Pages Posted: 4 Jan 2017

See all articles by Xiu Xu

Xiu Xu

Humboldt University of Berlin - Institute for Statistics and Econometrics

Cathy Chen

Humboldt University of Berlin

Wolfgang Karl Härdle

Blockchain Research Center Humboldt-Universität zu Berlin; Charles University; National Yang Ming Chiao Tung University; Asian Competitiveness Institute

Date Written: December 30, 2016

Abstract

Systemically important banks are connected and have dynamic dependencies of their default probabilities. An extraction of default factors from cross-sectional credit default swaps (CDS) curves allows to analyze the shape and the dynamics of the default probabilities. Extending the Dynamic Nelson Siegel (DNS) model, we propose a network DNS model to analyze the interconnectedness of default factors in a dynamic fashion, and forecast the CDS curves. The extracted level factors representing long-term default risk demonstrate 85.5% total connectedness, while the slope and the curvature factors document 79.72% and 62.94% total connectedness for the short-term and middle-term default risk, respectively. The issues of default spillover and systemic risk should be weighted for the market participants with longer credit exposures, and for regulators with a mission to stabilize financial markets. The US banks contribute more to the long-run default spillover before 2012, whereas the European banks are major default transmitters during and after the European debt crisis either in the long-run or short-run. The outperformance of the network DNS model indicates that the prediction on CDS curve requires network information.

Keywords: CDS, network, default risk, variance decomposition, risk management

JEL Classification: C32, C51, G17

Suggested Citation

Xu, Xiu and Chen, Cathy and Härdle, Wolfgang Karl, Dynamic Credit Default Swaps Curves in a Network Topology (December 30, 2016). SFB 649 Discussion Paper 2016-059, Available at SSRN: https://ssrn.com/abstract=2892551 or http://dx.doi.org/10.2139/ssrn.2892551

Xiu Xu

Humboldt University of Berlin - Institute for Statistics and Econometrics ( email )

Unter den Linden 6
Berlin, D - 10099
Germany

Cathy Chen

Humboldt University of Berlin ( email )

Unter den Linden 6
Berlin, AK Berlin 10099
Germany

Wolfgang Karl Härdle (Contact Author)

Blockchain Research Center Humboldt-Universität zu Berlin ( email )

Unter den Linden 6
Berlin, D-10099
Germany

Charles University ( email )

Celetná 13
Dept Math Physics
Praha 1, 116 36
Czech Republic

National Yang Ming Chiao Tung University ( email )

No. 1001, Daxue Rd. East Dist.
Hsinchu City 300093
Taiwan

Asian Competitiveness Institute ( email )

Singapore

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
105
Abstract Views
842
Rank
462,937
PlumX Metrics