Credit Default Spreads Research Articles

Dynamic credit risk transmissions among global major industries: Evidence from the TVP-VAR spillover approach

We examine the dynamics of credit risk connectedness by analyzing credit default spreads in four major sectors (banks, transportation, manufacturing, electricity) across three global regions (Asia, Europe, North America) using the TVP-VAR spillover methodology from 2007 to 2024. We have identified significant findings regarding credit risk spillovers among them. First, there are consistently high levels of credit risk spillovers between sectors, indicating underlying economic factors influencing the transmission of credit risk shocks. Second, notable regional findings include a substantial increase in credit risk connectedness for Asian banks during the global financial crisis (GFC). European manufacturing sectors also displayed significantly high connectedness levels during both the GFC and the COVID-19, while North American banks saw a notable surge due to the collapse of Silicon Valley Banks (SVB) in March 2023. In addition, during the RU-war, the electricity and manufacturing sectors in Europe had high CDS connectedness. Lastly, a distinct observation emerged concerning the Asian transportation sector. These findings have practical implications for policymakers and portfolio managers. For instance, they can help policymakers assess the effectiveness of their policies by revealing global industry credit risk interconnections. Additionally, the dynamic credit risk linkages provide strategies for hedging credit risk.

Default risk transmission in the travel and leisure industry

Default risk in the Travel and Leisure (T&L) industry remains understudied despite its implications for the industry’s health and stability. This paper investigates the transmission of default risk among US T&L firms over various credit horizons from July 22, 2008 to December 9, 2022, paying special attention to the impact of COVID-19. The short-, medium-, and long-term default risk factors are extracted from the Credit Default Spread (CDS) curve of the US T&L industry then used within a connectedness approach. The results reveal considerable default risk transmission, particularly in the long-term. Default risk transmission has spiked across all horizons since the pandemic, reflecting the deterioration in credit quality of T&L firms under the pandemic. Analysis of the drivers of default risk transmission shows that several macro-financial variables, especially news market sentiment and stock market volatility induced by the pandemic, have an important explanatory role.

Winds of tapering, financial gravity and COVID-19

Real interest rates have fallen dramatically since the early 1980s. Economic theory states that lower real rates discourage savings while promoting spending. However, today, in the world economy, we face a global saving glut problem in which, even in negative real rates, economic agents keep saving. This situation leads to excess demand for safe assets (US Treasuries), lower bond yields, and higher equity valuations. Thus, the world economy has become more dependent on major economies, especially the United States. In this research, we aim to measure the dependency of the world economy on United States monetary policy. We called this new methodology “financial gravity” and tried to quantify the nature by using panel data analysis. We define monetary dependency (financial gravity) by US Investment flows and their reaction against International Reserves, Credit Default Spreads (CDS), and Foreign Exchange Rates. Our empirical findings support that financial gravity is positively related to international reserves and negatively related to Credit Default Swap Spreads (CDS) and Foreign Exchange rates. We also analyzed the COVID-19 period and found that pandemics positively contributed to world reserve accumulation due to economic lock-down measures, fiscal stimulus packages (unemployment benefits), and decreased global spending.

The Stock and CDS Market Consequences of Political Uncertainty: The Arab Spring

ABSTRACT We investigate how political unrest affects asset prices in the context of the Arab Spring. Abnormal returns in the major stock-market indices of Arab Spring countries average −1.1% on key days of Arab Spring and abnormal changes in credit default spreads average 1.4%. There is significant reaction to region wide as well as local protests indicating a spillover with protests in neighboring countries affecting investors’ perception of local political instability and the pricing of assets. Once protests start locally, investors start paying more attention to what is happening at home than in the region. The significant stock market reaction to region-wide protests in Arab Spring countries indicates a spill-over where investors price an increase in the probability of political turmoil in one country when there are protests in neighboring countries. The decline in stock market indices coupled with the increase in credit default spreads indicates that investors anticipate and ex-ante price how current political uncertainty will affect firm value.

The maturity of sovereign debt issuance in the euro area.

We use information on new sovereign debt issues in the euro area to explore the drivers behind the debt maturity decisions of governments. We set up a theoretical model for the maturity structure that trades off the preference for liquidity services provided by short-term debt, roll-over risk and price risk. The average debt maturity is negatively related to both the level and the slope of the yield curve. A panel VAR analysis shows that positive shocks to risk aversion, the probability of non-repayment and the demand for the liquidity services of short-term debt all have a positive effect on the yield curve level and slope, and a negative effect on the average maturity of new debt issues. These results are partially in line with our theoretical framework. A forecast error variance decomposition suggests that changes in the probability of non-repayment as captured by the expected default frequency extracted from credit default spreads are the most important source of shocks.

The Maturity of Sovereign Debt Issuance in the Euro Area

We use information on new sovereign debt issues in the euro area to explore the drivers behind the debt maturity decisions of governments. We set up a theoretical model for the maturity structure that trades off the preference for liquidity services provided by short-term debt, roll-over risk and price risk. The average debt maturity is negatively related to both the level and the slope of the yield curve. A panel VAR analysis shows that positive shocks to risk aversion, the probability of non-repayment and the demand for the liquidity services of short-term debt all have a positive effect on the yield curve level and slope, and a negative effect on the average maturity of new debt issues. These results are partially in line with our theory. A forecast error variance decomposition suggests that changes in the probability of non-repayment as captured by the expected default frequency extracted from credit default spreads are the most important source of shocks.

Mandating Women on Boards: Evidence from the United States

On September 30, 2018, California became the first U.S. state to set quotas for women directors on corporate boards. The passage of this law resulted in a significant decline in shareholder value for firms headquartered in California. The decline in shareholder value is directly related to the number of female directors that firms are required to add under these quotas. We argue that supply-side constraints contribute to the costs imposed by the mandate. The expected costs of the quotas are higher for firms that face a more limited director pool and for those with weak corporate governance. Earnings forecasts for California firms also decline after the passage of the law. The law is associated with a widening of credit default spreads for affected firms, suggesting that differences in risk-taking preferences between male and female directors do not explain the results.

Connectedness between US industry level credit markets and determinants

We examine the connectedness between US industry-level credit markets, using both Credit Default Spread (CDS) changes and volatilities, over the period from December 17, 2007, to November 13, 2015. The total, net directional and pairwise spillovers are estimated based on the generalized VAR framework developed by Diebold and Yilmaz (2012). The empirical analysis shows strong interactions for CDS spread change and volatility among all ten industries. Consumer Services and Basic Materials are the significant risk transmitters. Economic policy uncertainty and different market volatilities significantly determine credit market risk spillovers which also increase during market turbulence situations indicating a possible contagion effect. Implications of the findings are discussed.

On the forward rate concept in multi-state life insurance

Similarly to the notion of modeling credit risk by using forward credit default spread rates, mortality risk in life insurance contracts is nowadays often modeled by using forward mortality (spread) rates. More recently, this concept has also been discussed for more complex life insurances that include multiple lives or intermediate states that correspond to the health status of the insured. For consistency purposes and for technical reasons, most authors assume that the underlying financial and demographic events are stochastically independent.

Dynamic relationship between Turkey and European countries during the global financial crisis

This study examines the relationship between time-varying risk perceptions of investors towards major European countries and Turkey. In that manner, we first obtain the dynamic conditional correlations between the credit default spreads (CDSs) of Turkey and 13 European countries from September 2004 to April 2013. Next, we endogenously detect the shifts in these dynamic correlation levels using a penalized contrast methodology. Accordingly, we find positive level shifts in all correlations following the US crisis. The upward trend in all CDS correlations holds during the eurozone debt crisis, but positive changes in correlations are not flagged as level shifts by the model, except in a few cases. The results suggest that Turkey is not immune to global financial conditions and there is integration between Turkey and the major European economies in terms of risk perception after the global financial crisis.

Parameter Estimation and Inference with Spatial Lags and Cointegration

We study dynamic panel data models where the long run outcome for a particular cross-section is affected by a weighted average of the outcomes in the other cross-sections. We show that imposing such a structure implies several cointegrating relationships that are nonlinear in the coefficients to be estimated. Assuming that the weights are exogenously given, we extend the dynamic ordinary least squares methodology and provide a dynamic two-stage least squares estimator. We derive the large sample properties of our proposed estimator and investigate its small sample distribution in a simulation study. Then our methodology is applied to US financial market data, which consist of credit default swap spreads, firm specific and industry data. A closeness measure for firms is based on input-output matrices. Our estimates show that this particular form of spatial correlation of credit default spreads is substantial and highly significant.

The Relationship between Credit Default Swap Spreads, Bond Yields, and Credit Rating Announcements

A company’s credit default swap spread is the cost per annum for protection against a default by the company. In this paper we analyze data on credit default swap spreads collected by a credit derivatives broker. We first examine the relationship between credit default spreads and bond yields and reach conclusions on the benchmark risk-free rate used by participants in the credit derivatives market. We then carry out a series of tests to explore the extent to which credit rating announcements by Moody’s are anticipated by participants in the credit default swap market.

Debt Valuation Adjustments and Executive Compensation

This paper investigates the relation between debt valuation adjustments (DVAs) and top executive compensation in the banking industry. DVAs arise from changes in fair value of liabilities associated with changes in a firm’s own credit standing, and have become a significant income component for some banking companies. We present three major findings. First, we find that executive compensation is positively related to pre-DVA income and stock returns, which is consistent with the relationships suggested by prior literature (e.g., Lambert and Larcker, 1987; Sloan, 1993). However, our second finding shows that top executives are penalized not only for DVA losses but also for DVA gains. This finding is consistent with the notion that efficient compensation contracts should be conservative and incorporate DVA losses immediately, while DVA gains could in fact be economic losses because the firm’s credit standing has declined. Consistent with this notion, we show that top executive compensation decreases in banks with increased Credit Default Spread (CDS) premiums (a proxy for declined own credit rating), but the explanation power of CDS is subsumed by DVA once DVA is added to the model. This finding implies that the compensation committees of banks penalize executives for DVA gains to discourage them from incurring economic losses resulting from credit rating deterioration.

Transmigration Across Price Discovery Categories: Evidence from the U.S. CDS and Equity Markets

For 174 U.S. firms between Jan 2005 and Dec 2009, we extract implied credit default spreads (ICDS) from daily stock prices using an improvised calibration of the RiskMetrics CreditGrade Model. Both ICDS and credit default swap spreads (CDS) reflect the price of credit risk. We confirm cointegration between ICDS and CDS for 173 firms. Using Gonzalo-Granger (1995) and Hasbrouck (1995) measures, we sort firms into one of five categories of credit risk price discovery contribution. We find the ICDS and CDS each performs the bulk of price discovery for a similar number of firms. However, a quarterly-rolling update of price discovery measures show the CDS market dominating price discovery for an increasing number of firms. Between 01-Jan-2005 and 30-Jun-2007, CDS dominates price discovery for 52 firms. But between 01-Jan-2006 and 30-Jun 2008, with the onset of the GFC, the number increases to 150 firms. As we move away from the height of the GFC, the number of firms is reduced into other categories, but remains high relative to the pre-GFC period. Our documented transmigration patterns can only come from analyzing a large cross-sectional sample of spot-derivative markets. Our finding is consistent with the Hong and Sraer (2011) argument that the lead-up to the GFC is described by cheap credit, low volatility and low turnover volume. Before mid-2007, CDS spreads are especially low and tranquil.We ascertain economic significance with portfolio strategies that draws trading signals from the CDS market. The profit/loss results show that the portfolio strategy conditional on identifying and updating the list of firms for which CDS dominates price discovery, is the most profitable against all other unconditional and conditional benchmarks.

The Term Structure of Credit Spreads: Theory and Evidence on Credit Default Swaps

Using a large data set on credit default swaps, we perform a joint analysis of the term structure of interest rates, credit spreads, and liquidity premia. We select reference companies that fall into two broad industry sectors and two broad credit rating classes. Within each sector and credit rating class, we divide the companies into two liquidity groups based on the quote updating frequency. We then study how the term structures of credit default risk premia differ across industry sectors, credit rating classes, and liquidity groups. We develop a class of dynamic term structure models that include two benchmark interest-rate factors, two credit risk factors for the high-liquidity groups, and an additional default risk factor and a liquidity risk factor that capture the difference between the two liquidity groups. We link these factors to the instantaneous benchmark interest rate and credit spread via both an affine function and a quadratic function, and compare their relative performance. We estimate the models using a three-step procedure. First, we estimate the interest-rate factor dynamics and the instantaneous interest rate function using the libor and swap rates. Second, we take the interest-rate factors and estimate the default-risk dynamics and the instantaneous credit spread function using the average credit default spreads of the high-liquidity group for each industry sector and credit rating class. Third, we identify an additional credit risk factor and a liquidity risk factor using the credit default swap spreads in the low-liquidity group. At each step, we cast the models into a state-space form and estimate the model parameters using quasi-maximum likelihood method. Estimation shows that the quadratic specifications generate better and more uniform performance across the term structure of interest rates and credit spreads. Furthermore, firms in different industry and credit rating classes have different default risk dynamics. Nevertheless, in all cases, default risks exhibit intricate dynamic interactions with the interest-rate factors. Interest-rate factors both predict the default risk and have a contemporaneous impact on it. Within each industry and credit rating class, the average credit default swap spreads for the high-liquidity group are significantly higher than for the low-liquidity group. Estimation shows that the difference is driven by both default risk and liquidity difference. The low-liquidity group has a lower default arrival rate, and also a much heavier discounting due to low liquidity.

The relationship between credit default swap spreads, bond yields, and credit rating announcements

A company’s credit default swap spread is the cost per annum for protection against a default by the company. In this paper we analyze data on credit default swap spreads collected by a credit derivatives broker. We first examine the relationship between credit default spreads and bond yields and reach conclusions on the benchmark risk-free rate used by participants in the credit derivatives market. We then carry out a series of tests to explore the extent to which credit rating announcements by Moody’s are anticipated by participants in the credit default swap market.