Credit Derivative Theory & Practice A Credit Primer & Review of the Impact of ISDA Standardization on Credit Default Swap Pricing & Credit Model Calibration

2018 ◽  
Author(s):  
Nicholas Burgess
Keyword(s):  
Model Calibration ◽  
Credit Default Swap ◽  
Credit Default ◽  
Credit Derivative ◽  
Default Swap ◽  
The Impact

scholarly journals The Impact of Earnings on the Pricing of Credit Default Swaps

2009 ◽  
Vol 84 (5) ◽  
pp. 1363-1394 ◽  
Author(s):  
Jeffrey L. Callen ◽  
Joshua Livnat ◽  
Dan Segal
Keyword(s):  
Default Risk ◽  
Credit Default Swap ◽  
Credit Default Swaps ◽  
Cash Flows ◽  
Earnings Surprises ◽  
Credit Default ◽  
Percent Increase ◽  
Default Swap ◽  
Highly Correlated ◽  
The Impact

ABSTRACT: This study evaluates the impact of earnings on credit risk in the Credit Default Swap (CDS) market using levels, changes, and event study analyses. We find that earnings (cash flows, accruals) of reference firms are negatively and significantly correlated with the level of CDS premia, consistent with earnings (cash flows, accruals) conveying information about default risk. Based on the changes analysis, a 1 percent increase in ROA decreases CDS rates significantly by about 5 percent. We also find that (1) CDS premia are more highly correlated with below-median earnings than with above-median earnings and (2) CDS premia are more highly correlated with earnings of low-rated firms than with earnings of high-rated firms. Evidence indicates further that short-window earnings surprises are negatively and significantly correlated with CDS premia changes in the three-day window surrounding the preliminary earnings announcement, although the impact is concentrated in the shorter maturities.

scholarly journals The Effect of Executive Compensation on Credit Default Swap Spread

2019 ◽  
Vol 21 (1) ◽  
pp. 19
Author(s):  
Meizaroh Meizaroh ◽  
Masripah Masripah
Keyword(s):  
Executive Compensation ◽  
Risk Taking ◽  
Time Series Data ◽  
Credit Default Swap ◽  
Best Interests ◽  
Series Data ◽  
Credit Default ◽  
Default Swap ◽  
Risk Taking Behavior ◽  
The Impact

Investors have been trying to formulate the optimum composition of executives’ compensation which will incentivize the executives to perform better and act in the shareholders’ best interests. This study aims to find empirical evidence about the impact of executive compensation on the default risk with the Credit Default Swap (CDS) spread as the proxy, using panel data to test the research model, which combines the analysis of cross-section and time series data. The study is conducted based on 1,416 observations of 177 U.S. companies from 2008-2015. The data are mainly collected from Datastream, Compustat, CRSP, and the US SEC’s EDGAR database. The current study provides a contribution by suggesting that executives’ compensation will trigger risk-taking behavior. The results of this study reveal, firstly, both equity-based compensation and debt-like compensation induce risk-taking behavior by the executives. Secondly, the correlation between both the form of the compensation and the CDS spread is weakened in a high information asymmetry environment. Lastly, this study finds that a CFO’s compensation has more influence on the CDS spread, compared to the other board executives, but this condition only occurs when the compensation is awarded in the form of debt-like compensation. To improve the generalization of the results, a further study may consider expanding the sample into several countries.

THE IMPACT OF STOCK RETURNS VOLATILITY ON CREDIT DEFAULT SWAP RATES: A COPULA STUDY

2005 ◽  
Vol 08 (08) ◽  
pp. 1135-1155 ◽  
Author(s):  
FATHI ABID ◽  
NADER NAIFAR
Keyword(s):  
Stock Returns ◽  
Stock Return ◽  
Credit Default Swap ◽  
Archimedean Copula ◽  
Return Volatility ◽  
Stock Return Volatility ◽  
Credit Default ◽  
Default Swap ◽  
The Impact ◽  
Swap Rates

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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