Determinants of Euro-Area Bank CDS Spreads

Maria-Eleni Agoraki, Dimitris Georgoutsos and George T. Moratis

Chapter 60 in Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning:(In 4 Volumes), 2020, pp 2161-2198 from World Scientific Publishing Co. Pte. Ltd.

Abstract: This study relies on a structural approach model to investigate the determinants of Credit Default Swap (CDS) spread changes for Euro-zone’s financial institutions over the period January 2005 to October 2015. Going beyond the structural model, this study incorporates features such as the role of systemic risk factors, bank-specific characteristics and credit ratings. We adopt the dynamic framework provided by panel Vector Autoregressive Models which allows for endogeneity issues and this is a novelty of our approach. The main findings are that structural models seem to be more relevant during high volatile periods and that the relation between the CDS and its theoretical determinants is not constant over time. Overall, the empirical results suggest that structural models perform well in explaining bank credit risk, but determinants of CDS also rely on the underlying economic situation which should be taken into consideration when interpreting CDS spread changes.

Keywords: Financial Econometrics; Financial Mathematics; Financial Statistics; Financial Technology; Machine Learning; Covariance Regression; Cluster Effect; Option Bound; Dynamic Capital Budgeting; Big Data (search for similar items in EconPapers)
JEL-codes: C01 C1 G32 (search for similar items in EconPapers)
Date: 2020
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