scholarly journals How Sovereign Is Sovereign Credit Risk?

2011 ◽  
Vol 3 (2) ◽  
pp. 75-103 ◽  
Author(s):  
Francis A Longstaff ◽  
Jun Pan ◽  
Lasse H Pedersen ◽  
Kenneth J Singleton

We study the nature of sovereign credit risk using an extensive set of sovereign CDS data. We find that the majority of sovereign credit risk can be linked to global factors. A single principal component accounts for 64 percent of the variation in sovereign credit spreads. Furthermore, sovereign credit spreads are more related to the US stock and high-yield markets than they are to local economic measures. We decompose credit spreads into their risk premium and default risk components. On average, the risk premium represents about a third of the credit spread. (JEL F34, G15, O16, O19, P34)

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Filippo Gori

Purpose This paper aims to investigate the nexus between banks’ foreign assets and sovereign default risk in a panel of 15 developed economies. The empirical evidence suggests that banks’ foreign exposure is an important determinant of sovereign default probability. Design/methodology/approach Using data from the consolidated banking statistics (total foreign claims on ultimate risk basis) by the Bank of International Settlements, the author constructs a measure of bank international exposure to peer countries. This measure is then used as the target variable in a panel regression for sovereign credit default swaps. The model includes 15 European and non-European developed economies. Identification is discussed extensively in the paper. Findings Quantitatively, a 1% increase in banks’ cross-border claims increases sovereign default risk by about 0.19%. The relationship is weaker when banks are more capitalised. On the other hand, governments are more vulnerable to credit risk spillovers from banks’ international portfolios when having higher debt to GDP ratios. Originality/value To the best of the author’s knowledge, this is the first paper that attempts explicitly to establish an empirical connection between banks’ international assets and sovereign default risk. To the author’s opinion, this paper represents a contribution to our understanding of how sovereign credit risk spills over across countries. It also extends significantly the existing literature on the determinants of sovereign risk (that primarily focused on fundamentals, market characteristics – such as liquidity – and global factors). This paper ultimately sheds some new light on the role of intermediaries in the international transmission of credit risk, also adding to today’s discussion about the linkages between banks and sovereigns.


2015 ◽  
Vol 02 (03) ◽  
pp. 1550026
Author(s):  
Min Zhang ◽  
Adam W. Kolkiewicz ◽  
Tony S. Wirjanto ◽  
Xindan Li

In this paper, we investigate the nature of sovereign credit risk for selected Asian and European countries based on a set of sovereign CDS data over an eight-year period that includes the episode of the 2007–2008 global financial crisis. Our results indicate that there exists strong commonality in sovereign credit risk among the countries studied in this paper following the crisis. In addition, our results also show that commonality is importantly associated with both local and global financial and economic variables. However, there are markedly different impacts of the sovereign of credit risk in Asian and European countries. Specifically, we find that foreign reserve, global stock market, and volatility risk premium, affect Asian and European sovereign credit risks in the opposite direction. Lastly, we model the arrival rates of credit events as a square-root diffusion process from which a pricing model is constructed and estimated over pre- and post-crisis periods. Then the resulting model is used to decompose credit spreads into risk premium and credit-event components. For most countries in our study, credit-event components appear to weight more than risk-premiums.


2020 ◽  
Vol 12 (2) ◽  
pp. 137-154
Author(s):  
Zornitsa Todorova ◽  

This paper applies novel tools from spatial econometrics to measure, quantifyand predict sovereign CDS spreads. Network risk is modelled by making each sovereignísCDS spread a function of the CDS spreads of its ìneighborsî in the Önancial network. Themain Öndings of the paper are: (1) the network model improves forecasting accuracy by 15% to 20%; (2) exogenous Önancial shocks propagate in the network of sovereigns and 40 %to 50% of the total e§ect is due to indirect (network) e§ects. These Öndings suggest analternative explanation to the well-known credit spread puzzle. To rationalize the Öndingsthe paper develops a simple structural network model of sovereign credit risk with Önancialcross-holdings and multiple equilibria.


Author(s):  
Patrick Augustin ◽  
Valeri Sokolovski ◽  
Marti G. Subrahmanyam ◽  
Davide Tomio

2014 ◽  
Vol 90 (2) ◽  
pp. 641-674 ◽  
Author(s):  
Pepa Kraft

ABSTRACT I examine a dataset of both quantitative (hard) adjustments to firms' reported U.S. GAAP financial statement numbers and qualitative (soft) adjustments to firms' credit ratings that Moody's develops and uses in its credit rating process. I first document differences between firms' reported and Moody's adjusted numbers that are both large and frequent across firms. For example, primarily because of upward adjustments to interest expense and debt attributable to firms' off-balance sheet debt, on average, adjusted coverage (cash flow-to-debt) ratios are 27 percent (8 percent) lower and adjusted leverage ratios are 70 percent higher than the corresponding U.S. GAAP ratios. I then find that Moody's hard and soft rating adjustments are associated with significantly higher credit spreads and flatter credit spread term structures. Overall, the results indicate that Moody's quantitative adjustments to financial statement numbers and qualitative adjustments to credit ratings enable it to better capture default risk, consistent with it effectively processing both hard and soft information.


2021 ◽  
pp. 102127
Author(s):  
Sawan Rathi ◽  
Sanket Mohapatra ◽  
Arvind Sahay

Sign in / Sign up

Export Citation Format

Share Document