How do “gatekeepers” affect credit risk?

This study investigates the relationship between auditor tenure and credit default swap (CDS) spreads of U.S. firms based on quantile regression. After allowing for common determinants of CDS spreads, auditor tenure exerts both statistically and economically significant additional impacts on the CDS market. Furthermore, there are differential effects of common CDS spread determinants and auditor tenure. While common determinants of CDS spreads (e.g., leverage, volatility, risk free rate, credit ratings, and earnings) have monotonically increasing impacts when CDS spreads (and their changes) are increasingly higher, auditor tenure primarily has the impact when CDS spreads are of low or median levels for less risky firms.     

The impact of central clearing on the market for single-name credit default swaps

In this article, we revisit the impact of the voluntary central clearing scheme on the CDS market. In order to address the endogeneity problem, we use a robust methodology that relies on dynamic propensity-score matching combined with generalized difference-in-differences. Our empirical findings show that central clearing results in a small increase in CDS spreads (ranging from 14 to 19 bps), while there is no evidence of an associated improvement in CDS market liquidity and trading activity or of a deterioration in the default risk of the underlying bond. These results suggest that the increase in CDS spreads can be mainly attributed to a reduction in CDS counterparty risk.     

Credit default swaps and sovereign debt markets

This study investigates the link between the price discovery dynamics in sovereign credit default swaps (CDS) and bond markets and the degree of financial integration of emerging markets. Using CDS and sovereign bond spreads, the price discovery mechanism was tested using a vector error correction model. Financial integration is measured using news-based methods. We find that sovereign CDS and bond markets are co-integrated. In five out of seven sovereigns (71%), the bond market leads in price discovery by adjusting to new information regarding credit risk before CDS. In 29% of times, CDS markets are the source of price discovery. We also find a positive correlation of 0.67 between the degree of financial integration and the bond market information share. The evidence suggests that changes in sovereign credit risk and bond yields are significantly influenced by common external (global) factors, while country-specific factors play an insignificant role.     

Analyzing credit risk transmission to the nonfinancial sector in Europe: A network approach

We use a factor model and elastic net shrinkage to model a high-dimensional network of European credit default swap (CDS) spreads. Our empirical approach allows us to assess the joint transmission of bank and sovereign risk to the nonfinancial corporate sector. Our findings identify a sectoral clustering in the CDS network, where financial institutions are in the center and nonfinancial entities as well as sovereigns are grouped around the financial center. The network has a geographical component reflected in different patterns of real-sector risk transmission across countries. Our framework also provides dynamic estimates of risk transmission, a useful tool for systemic risk monitoring.     

Information transmission between sovereign debt CDS and other financial factors ⿿ The case of Latin America

This paper extends previous research by investigating the intertemporal causality relationships between daily Latin America sovereign credit default swap (CDS) returns and other financial sovereign debt spread determinants. The empirical results indicate that information in sovereign CDS can both lead and lag these financial determinants. Specifically, country financial variables, including exchange rates and lending spreads, and global financial variables including 10-U.S. Treasury yields, VIX and TED spreads, are important determinants for future sovereign CDS price movements. The findings provide investment implications for international financial markets.     

Asymmetric convergence in US financial credit default swap sector index markets

This study examines the asymmetric adjustments to the long-run equilibrium for credit default swap (CDS) sector indexes of three financial sectors – banking, financial services and insurance – in the presence of a threshold effect. The results of the momentum-threshold autoregression (M-TAR) models demonstrate that asymmetric cointegration exists for all pairs comprised of those three CDS indexes. The speeds of adjustment in the long-run are much higher in the case of adjustments from below the threshold than from above for all the pairs. The estimates of The MTAR-VEC models suggest that the dual CDS index return in each sector pair participates in the adjustment to equilibrium in the short- and long-run taken together. But in the long-run alone, only one of the two spreads in each pair participates. Policy implications are also provided.     

Systemic risk in European financial and energy sectors: Dynamic factor copula approach

We perform an analysis of systemic risk in financial and energy sectors in Europe using daily time series of CDS spreads. We employ the factor copula model with GAS dynamics from Oh and Patton (2018) for the purpose of estimating dependency structures between market participants. Based on the estimated models, we perform Monte Carlo simulations to obtain future values of CDS spreads, and then measure the probability of systemic events at given time points. We conclude that substantially higher systemic risk is present in the financial sector compared to the energy sector. We also find that the most systemically vulnerable financial and energy companies come from Spain.     

Endogenous trading in credit default swaps

We introduce a real options model in order to quantify the moral hazard impact of credit default swap (CDS) positions on the corporate default probabilities. Moral hazard is widely addressed in the insurance literature, where the insured agent may become less cautious about preventing the risk from occurring. Importantly, with CDS the moral hazard problem may be magnified since one can buy multiple protections for the same bond. To illustrate this issue, we consider a firm with the possibility of switching from an investment to another one. An investor can influence the strategic decisions of the firm and can also trade CDS written on the firm. We analyze how the decisions of the investor influence the firm value when he is allowed to trade credit default contracts on the firm’s debt. Our model involves a time-dependent optimal stopping problem, which we study analytically and numerically, using the Longstaff–Schwartz algorithm. We identify the situations where the investor exercises the switching option with a loss, and we measure the impact on the firm’s value and firm’s default probability. Contrary to the common intuition, the investors’ optimal behavior does not systematically consist in buying CDSs and increase the default probabilities. Instead, large indifference zones exist, where no arbitrage profits can be realized. As the number of the CDSs in the position increases to exceed several times the level of a complete insurance, we enter in the zone where arbitrage profits can be made. These are obtained by implementing very aggressive strategies (i.e., increasing substantially the default probability by producing losses to the firm). The profits increase sharply as we exit the indifference zone.     

Measuring connectedness of euro area sovereign risk

We introduce a method for measuring the default risk connectedness of euro zone sovereign states using credit default swap (CDS) and bond data. The connectedness measure is based on an out-of-sample variance decomposition of model forecast errors. Due to its predictive nature, it can respond to crisis occurrences more quickly than common in-sample techniques. We determine the sovereign default risk connectedness using both CDS and bond data in order to obtain a more comprehensive picture of the system. We find evidence that there are several observable factors that drive the difference between CDS and bonds, but both data sources still contain specific information for connectedness spill-overs. In general, we can identify countries that impose risk on the system and the respective spill-over channels. Our empirical analysis covers the years 2009–2014, such that the recovery paths of countries exiting EU and IMF financial assistance schemes and the responses to the ECB’s unconventional policy measures can be analyzed.     

A vector-autoregression analysis of credit and liquidity factor dynamics in US LIBOR and Euribor swap markets

We use a vector autoregressive approach to investigate the determinants of US Dollar LIBOR and Euribor swap spread variation during the 2007–2009 crisis in global credit and money markets. Using market-quoted yield and spread data from the highly liquid credit default swap (CDS) and overnight index swap (OIS) markets, we provide compelling empirical evidence that liquidity risk factor shocks have been the dominant drivers of the variation in swap spreads over this period. Our findings provide an explanation for the temporal differences that liquidity shocks have on swap spreads and provide a contemporary perspective on the dynamical interplay between credit-default and liquidity risk-factors in these markets. As all our risk-factor proxies are traded in liquid derivatives markets, our findings have implications for proprietary hedge fund traders hedging an exposure to swap-spread risk, for bank treasurers managing their liquidity requirements and for central bankers seeking to better understand the response of markets to their macroeconomic policy implementation and liquidity management actions. Indeed our markets-based analysis suggests that the European Central Bank (ECB) has underperformed relative to the Federal Reserve in terms of the differing levels of market confidence placed in its macroeconomic policy actions and remedial liquidity interventions during the period.     

Interconnectedness and systemic risk in the US CDS market

This study assesses systemic risk in the US credit default swap (CDS) market. First, this study estimates the bilateral exposures matrix using aggregate fair value data and theoretically analyze interconnectedness in the US CDS network using various network measures. Second, this study theoretically analyzes the contagious defaults. The default analysis shows the theoretical occurrence of many stand-alone defaults and one contagious default via the CDS network during the global financial crisis. A stress test based on a hypothetical severe stress scenario predicts almost no future contagious defaults. Thus, risk contagion via the CDS network is unlikely.     

Assessment of time-varying systemic risk in credit default swap indices: Simultaneity and contagiousness

This study assesses systemic risk inherent in credit default swap (CDS) indices using empirical and statistical analyses. We define systemic risk in two perspectives: the possibilities of simultaneous and contagious defaults, and then quantify them separately across benchmark models. To do so, we employ a Marshall-Olkin copula model to measure simultaneous default risk, and an interacting intensity-based model to capture contagious default risk. For an empirical test, we collect daily data for the iTraxx Europe CDS index and its tranche prices in the period from 2005 to 2014, and calibrate model parameters varying across time. In addition, we select forecasting models that have minimal prediction errors for the calibrated time series. Finally, we identify significant changes in each dynamic of systemic risk indicator before and after default and downgrade-related episodes that have occurred in the global financial crisis and European sovereign debt crisis.     

Mutual excitation in Eurozone sovereign CDS

We study self- and cross-excitation of shocks in the Eurozone sovereign CDS market. We adopt a multivariate setting with credit default intensities driven by mutually exciting jump processes, to capture the salient features observed in the data, in particular, the clustering of high default probabilities both in time (over days) and in space (across countries). The feedback between jump events and the intensity of these jumps is the key element of the model. We derive closed-form formulae for CDS prices, and estimate the model by matching theoretical prices to their empirical counterparts. We find evidence of self-excitation and asymmetric cross-excitation. Using impulse-response analysis, we assess the impact of shocks and a potential policy intervention not just on a single country under scrutiny but also, through the effect on cross-excitation risk which generates systemic sovereign risk, on other interconnected countries.     

Spillovers among CDS indexes in the US financial sector

By employing the robust cross-correlation function approach proposed by Hong (2001), and conducting pre-tests for structural breaks in the variances as well as removing the causality-in-mean effects in the causality-in-variance tests, we investigate volatility and mean transmissions between the credit default swaps (CDS) indexes of three US financial sectors. We use daily series on five-year banking, insurance, and financial services sector CDS indexes at the sector level from January 2004 to December 2011. We find evidence of significant causality-in-mean effects running from the banking sector to the insurance and financial services sector CDS indexes and from the financial services to the insurance sector CDS indexes, suggesting the leading role of the banking and financial services sectors in terms of price discovery. Moreover, we find significant causality-in-variance effects from the financial services sector CDS index to that of the banking sector, implying the existence of information transmission and contagion from the former, the least regulated of the three. The implications of these findings on traders and policymakers are also provided.     

Credit risk and asymmetric information: A simplified approach

We present a simple model for risky, corporate debt. Debtholders and equityholders have incomplete information about the financial state of the debt issuing company. Information is incomplete because it is delayed for all agents, and it is asymmetrically distributed between debtholders and equityholders. We solve for the equityholders' optimal default policy and for the credit spreads required by debtholders. Delayed information accelerates the equityholders' optimal decision to default. Interestingly, this effect is small, implying only a small impact on credit spreads. Asymmetric information, however, has a major impact on credit spreads. Our model predicts high credit spreads for short-term debt, as observed empirically in credit markets.     

News sentiment,credit spreads,and information asymmetry

This paper examines how the sentiment of firm-specific news affects CDS spreads conditional on the degree of information asymmetry. Using a large set of news releases, we document a strong negative relationship between the sentiment of firm-specific news and CDS spreads. More importantly, consistent with the role of public news in reducing information asymmetry, we find evidence that the relation between news sentiment and CDS spreads is stronger for firms with higher information asymmetry. Furthermore, the relation is stronger for news with negative sentiment and during the 2008 financial crisis. Our results are robust to alternative sentiment measures.     

ESTIMATING FISCAL LIMITS: THE CASE OF GREECE

This paper uses Bayesian methods to estimate a real business cycle model that allows for interactions among fiscal policy instruments, the stochastic ‘fiscal limit’ and sovereign default. Using the particle filter to perform likelihood‐based inference, we estimate the full nonlinear model with post‐EMU data until 2010:Q4. We find that (i) the probability of default on Greek debt was in the range of 5–10% in 2010:Q4 and (ii) the 2011 surge in the Greek real interest rate is within model forecast bands. The results suggest that a nonlinear rational expectations environment can account for the Greek interest rate path. Copyright © 2014 John Wiley & Sons, Ltd.     

The COVID-19 Pandemic and Sovereign Bond Risk

Governments around the world are tackling the COVID-19 pandemic with a mix of public health, fiscal, macroprudential, monetary, and/or market-based policies. We assess the impact of the pandemic in Europe on sovereign CDS spreads using an event study methodology. We find that a higher number of cases and deaths and public health containment responses significantly increase the uncertainty among investors in European government bonds. Other governmental policies magnify the effect in the short run as supply chains are disrupted. Moreover, an increased debt-to-GDP ratio significantly boosts the cumulative abnormal change of CDS spreads, which indicates that investors are concerned about countries that are too indebted and thus have a limited capacity to intervene and provide fiscal stimuli and emergency fiscal packages to businesses and households.     

Credit Default Swaps: Risk Hedge or Financial Weapon of Mass Destruction?

Credit default swaps (CDSs) are contracts between buyers and sellers of protection against default. They are a form of debt insurance, or more precisely derivatives contracts that investors buy to either insure against or profit from a default. In this way CDS contracts act as a form of debt insurance in that they provide a means of protection against credit risk. In the aftermath of the global financial crisis, the CDS earned the reputation of a ‘financial weapon of mass destruction’. Why? Is this charge justified? This paper shows that the reality is more complex: CDSs carry benefit as well as costs, and the risks associated with them can be mitigated through prudent supervision.     

Identifying the true nature of price discovery and cross-market informational flow in the investment grade CDS and equity markets

We examine the comparative efficiency of systematic investment grade credit default swap (CDS) and equity markets using a time-varying coefficient vector autoregression. This modeling framework enables a view of cross-market informational flow along each point in the time-period under investigation by taking into account parameter instability. We obtain smoothing estimates of parameters capturing such flow between CDS and equity markets using daily data from 2004 to 2019, and measure the strength of flow via relative predictive gains. In contrast to prior studies, we find a two-way interactive effect in which certain types of information are captured more efficiently in prices by each market. We also find that the time-varying coefficient vector autoregression results in superior forecasting gains relative to models not accounting for price discovery. These results have implications for systematic investors, arbitrageurs and stakeholders who monitor systematic markets for their informational content.