Credit Spreads, Factors and Noise

Equities, Credits and Volatilities: A Multivariate Analysis of the European Market During the Sub-Prime Crisis

Structural Models of Credit Risk are Useful: Evidence from Hedge Ratios on Corporate Bonds

We analyse the relationship between credit default swap (CDS), bond and stock markets during 2000–2002. Focusing on the intertemporal co‐movement, we examine monthly, weekly and daily lead‐lag relationships in a vector autoregressive model and the adjustment between markets caused by cointegration. First, we find that stock returns lead CDS and bond spread changes. Second, CDS spread changes Granger cause bond spread changes for a higher number of firms than vice versa. Third, the CDS market is more sensitive to the stock market than the bond market and the strength of the co‐movement increases the lower the credit quality and the larger the bond issues. Finally, the CDS market contributes more to price discovery than the bond market and this effect is stronger for US than for European firms.

This paper documents an increase in the comovement between credit default swap (CDS) spread changes during the 2007–2009 crisis and investigates the source of that increase. One possible explanation is that comovement increased because fundamental values became more correlated. However, I find that changes in fundamentals account for only 23% of the increase in covariance. The remaining increase is attributed to changes in liquidity and the market price of default risk. In contrast, counterparty risk played an insignificant role. Although both contributed, the increase in covariance was driven more by variation in exposures than factor variance–covariance.

Sovereign credit default swap (CDS) spreads exhibit strong co-movements across Asian countries and regions, including both emerging and developed economies. After controlling for global impacts, we examine the regional lead-lag relationships among changes in ten Asian sovereign CDS spreads. We use the pairwise Granger causality test to find that lagged changes in Kazakhstan’s sovereign CDS spreads significantly predict changes in other Asian sovereign CDS spreads. By estimating the news-diffusion model, we find evidence that this predictive relationship may be explained by information diffusion. Furthermore, we find that lagged changes in Kazakhstan’s CDS spreads have significant out-of-sample predictive power for other Asian economies, providing practical implications for sustainable investments and risk management.

Credit default swap (CDS) spreads measure the default risk of the reference entity and have been frequently used in recent empirical papers. To provide a rigorous econometrics foundation for empirical CDS analysis, this paper applies the augmented Dickey–Fuller, Phillips–Perron, Kwiatkowski–Phillips–Schmidt–Shin, and Ng–Perron tests to study the unit root property of CDS spreads, and it uses the Phillips–Ouliaris–Hansen tests to determine whether they are cointegrated. The empirical sample consists of daily CDS spreads of the six large U.S. banks from 2001 to 2018. The main findings are that it is log, not raw, CDS spreads that are unit root processes, and that log CDS spreads are cointegrated. These findings imply that, even though the risks of individual banks may deviate from each other in the short run, there is a long-run relation that ties them together. As these CDS spreads are an important input for financial systemic risk, there are at least two policy implications. First, in monitoring systemic risk, policymakers should focus on long-run trends rather than short-run fluctuations of CDS spreads. Second, in controlling systemic risk, policy measures that reduce the long-run risks of individual banks, such as stress testing and capital buffers, are helpful in mitigating overall systemic risk.

In this work, we introduce a general framework for incorporating stochastic recovery into structural models. The framework extends the approach to recovery modeling developed in Cohen and Costanzino (2015, 2017) and provides for a systematic way to include different recovery processes into a structural credit model. The key observation is a connection between the partial information gap between firm manager and the market that is captured via a distortion of the probability of default. This last feature is computed by what is essentially a Girsanov transformation and reflects untangling of the recovery process from the default probability. Our framework can be thought of as an extension of Ishizaka and Takaoka (2003) and, in the same spirit of their work, we provide several examples of the framework including bounded recovery and a jump-to-zero model. One of the nice features of our framework is that, given prices from any one-factor structural model, we provide a systematic way to compute corresponding prices with stochastic recovery. The framework also provides a way to analyze correlation between Probability of Default (PD) and Loss Given Default (LGD), and term structure of recovery rates.

Abstract/Zusammenfassung The spread risk premium component of credit default swap (CDS) spreads represents a compensation demanded by protection sellers for future changes in CDS spreads caused by unpredictable fluctuations in the reference entity’s risk-neutral default intensity. This paper defines and estimates a measure of the spread risk premium component in CDS spreads of a sample of European investment-grade firms by using a stochastic intensity credit model. Our results show that, on average, investors demand a positive premium for such mark-to-market risks. After controlling for CDS market conditions, like liquidity and supply/demand effects, a panel data analysis of the estimated spread risk premia reveals a positive impact of event risk captured by the overall stock market volatility and a negative impact of investors’ appetite for exposure to credit markets as reflected by the overall CDS market. Marktrisikopr mien in Credit Default Swaps von Unternehmen Die Marktrisikopramie im Credit Default ...

In this study, we empirically investigate the relationship between credit default swap (CDS) spreads and financial market indicators belonging to bond, equity, and foreign exchange markets for the selected emerging market countries. This study has several findings. The empirical results suggest that the CDS spreads have a cointegrating relationship with the remaining financial market indicators for the whole sample. Another finding that deserves particular attention is that in the long run, the CDS spread is negatively related with the CDS market uncertainties. We argue that this negative relationship indicates low liquidity in the elevated uncertainty, which decreases CDS prices. The time-varying effects of each variable on the CDS spread are in line with the results obtained from the cointegration analyses. These findings have several implications for investors and policymakers in emerging market countries.

This study aims to investigate the existence of contagion between liquid and illiquid assets in the credit default swap (CDS) market around the recent financial crisis. The authors perform analyses based on vector autoregression model and the dynamic conditional correlation model. The estimation of vector autoregression models reveals that changes in liquid CDS (LCDS) spreads lead to changes in illiquid CDS spreads at least one week ahead during the financial crisis period, whereas the leading direction is reversed during the post-crisis period. Moreover, the results are robust after controlling for structural variables which are proven as determinants of CDS spreads and are empirically supported. This study interprets that information was incorporated first into the LCDSs because of the flight-to-liquidity during the recent crisis period but there is a default contagion effect by reflecting illiquidity-induced credit risk after the crisis. Finally, the dynamic conditional correlation analysis also confirms the main results.

Accounting Transparency and the Term Structure of Credit Spreads

In times of distress when a country loses access to markets, there is evidence that credit default swap (CDS) spreads are a leading indicator for sovereign risk than the EMBI+ sub-index for the country. However, it is not easy to discern the variables that determine the level of CDS spreads in Emerging Markets (EM); traders only quote the CDS spreads and not the inputs that are required to calculate such spreads. This note provides some evidence from Argentina and Brazil that reveals inconsistency between theory and practice in pricing CDS spreads in EM. This note suggests an alternate methodology that links CTD (cheapest-to-deliver) bonds to recovery values assumed in CDS contracts. Furthermore, special features that pertain to CDS contracts (repo specialness, short squeezes by central banks) may also magnify the financial distress of a sovereign.

This paper presents a modified version of Leland and Toft's [J. Finance, 1996, 51, 987–1019] structural credit risk model, together with a novel calibration methodology based on stock and CDS data: the firm asset value and volatility are consistently derived from equity prices; the default barrier is calibrated from CDS premia. It empirically shows that as long as the appropriate default barrier is selected, the model generates time series of stock market implied credit spreads that fit the times series of CDS spreads. Moreover, CDS implied default barriers prove to be consistent with stockholders’ rationality, with predictions made by structural models with endogenous default, and with historical recovery rates.

We use Google internet search volumes to measure households’ pessimism about overall market-wide credit health in the economy and show that this “household default sentiment” is positively correlated with the credit default swap (CDS) spread level in the market. However, while household default sentiment might drive the cost of credit to some degree, either directly or indirectly through its effect on the stock market, we find the stock market’s opinion about the credit risk in the economy (default probabilities backed out from structural models) to be much more important in explaining credit spreads. The rather weak link between household sentiment and CDS spreads, meanwhile, is consistent with the almost complete absence of retail investors (households) in the institutional investor-dominated credit derivatives market. The results are essentially the same, whether we look at market-wide CDS indexes or single-name CDS contracts, and whether we exclude the financial crisis or not.

This paper investigates the impact of infectious diseases on the evolution of sovereign credit default swap (CDS) spreads for a panel of 77 countries. Using annual data over 2004–2020, we find that infectious‐disease outbreaks have no discernible effect on CDS spreads, after controlling for macroeconomic and institutional factors. However, a granular analysis using high‐frequency data indicates that the COVID‐19 pandemic has had a significant impact on CDS spreads. This adverse effect appears to be more pronounced in advanced economies, which may reflect the greater severity of the pandemic and depth of the economic crisis in these countries, at least during the initial stage of the outbreak, as well as underreporting in developing countries due to differences in testing availability and institutional capacity. While more stringent containment measures help lower sovereign CDS spreads, the fiscal burden of these efforts could undermine credit worthiness and eventually push the cost of borrowing higher.