Debt Rollover Risk, Credit Default Swap Spread and Stock Returns: Evidence from the COVID-19 Crisis

Author(s):  
Ya Liu ◽  
Buhui Qiu ◽  
Teng Wang
2007 ◽  
Vol 15 (4) ◽  
pp. 450-463
Author(s):  
Halit Gonenc ◽  
Floris Schorer ◽  
Willem P.F. Appel

2020 ◽  
pp. 097215091988617
Author(s):  
Alessandra Ortolano ◽  
Eliana Angelini

The article analyses banks’ credit default swap (CDS) spread determinants, in light of the Eurozone debt crisis. The attention to this aspect is due to the very linkage between banking and sovereign sectors particularly evident during the aforementioned crisis. The study is conducted on a sample of Eurozone banks over the period 2009–2014 through a feasible generalized least squares (FGLS) linear panel data regression. The variables adopted are both balance sheet ratios and macroeconomic factors. The main results confirm the attention pointed at the influence of public conditions to the banking sector, as proved by the significance of variables like the 10-year bond yields or the long-term sovereign rating. It is also interesting to observe the output dealing with public debt, which may suggest opportunities not only of investment but also of speculation for banks on the debt itself. Balance sheet ratios, instead, are not significant. Our study is an additional contribution to the strand of literature that analyses the strong interconnections between the riskiness of banks and the public sector and it is a suggestion to proceed the research with a deeper analysis on systemic risk and its impact on banking CDS spread.


2005 ◽  
Vol 08 (08) ◽  
pp. 1135-1155 ◽  
Author(s):  
FATHI ABID ◽  
NADER NAIFAR

The aim of this paper is to study the impact of stock returns volatility of reference entities on credit default swap rates using a new dataset from the Japanese market. The majority of empirical research suggests the inadequacy of multinormal distribution and then the failure of methods based on correlation for measuring the structure of dependency. Using a copula approach, we can model the different relationships that can exist in different ranges of behavior. We study the bivariate distributions of credit default swap rates and the measure of stock return volatility estimated with GARCH (1,1) and focus on one parameter Archimedean copula. Starting from the empirical rank correlation statistics (Kendall's tau and Spearman's rho), we estimate the parameter values of each copula function presented in our study. Then, we choose the appropriate Archimedean copula that better fit to our data. We emphasize the finding that pairs with higher rating present a weaker dependence coefficient and then, the impact of stock return volatility on credit default swap rates is higher for the lowest rating class.


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