THE STOCHASTIC INTENSITY SSRD MODEL IMPLIED VOLATILITY PATTERNS FOR CREDIT DEFAULT SWAP OPTIONS AND THE IMPACT OF CORRELATION

2006 ◽  
Vol 09 (03) ◽  
pp. 315-339 ◽  
Author(s):  
DAMIANO BRIGO ◽  
LAURENT COUSOT

In this paper we investigate implied volatility patterns in the Shifted Square Root Diffusion (SSRD) model as functions of the model parameters. We begin by recalling the Credit Default Swap (CDS) options market model that is consistent with a market Black-like formula, thus introducing a notion of implied volatility for CDS options. We examine implied volatilities coming from SSRD prices and characterize the qualitative behavior of implied volatilities as functions of the SSRD model parameters. We introduce an analytical approximation for the SSRD implied volatility that follows the same patterns in the model parameters and that can be used to have a first rough estimate of the implied volatility following a calibration. We compute numerically the CDS-rate volatility smile for the adopted SSRD model. We find a decreasing pattern of SSRD implied volatilities in the interest-rate/intensity correlation. We check whether it is possible to assume zero correlation after the option maturity in computing the option price.

2009 ◽  
Vol 84 (5) ◽  
pp. 1363-1394 ◽  
Author(s):  
Jeffrey L. Callen ◽  
Joshua Livnat ◽  
Dan Segal

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.


2019 ◽  
Vol 21 (1) ◽  
pp. 19
Author(s):  
Meizaroh Meizaroh ◽  
Masripah Masripah

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.


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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