Credit Default Swap Research Articles

Identifying policy determinants of bank default risk during the COVID-19 pandemic: empirical evidence from the U.S. and Canada

ABSTRACT This study examines the policy determinants of bank default risk, proxied by credit default swap (CDS) spreads, using quarterly data from the U.S. and Canada for the period 2020 to 2022. The analysis considers four determinant groups: the COVID-19 pandemic shock, aggressive monetary and fiscal policy responses, macroprudential-related bank financial fundamentals, and macroeconomic and market conditions. Utilizing General Least Squares (GLS) and dynamic panel models with system General Method of Moments (GMM), the findings reveal that rising COVID-19 deaths significantly widen CDS spreads. Expansionary monetary policies reduce bank default risk, though the effectiveness under conventional monetary policy is reduced by increasing COVID-19 deaths. In contrast, expansionary fiscal policies and inflation broaden CDS spreads. The combined analysis highlights policy stances as dominant factors, with macroprudential-related fundamentals having minimal impact. The findings are robust using both 5-year and 10-year CDS measures. This study has significant policy implications during health and economic crises. For financial stability, policymakers should prioritize reducing pandemic-related deaths, utilize expansionary monetary policies with health support strategies, balance fiscal support to avoid excessive government spending, and implement measures to control inflation. It is essential to enhance coordination between healthcare, fiscal, and monetary authorities for effective policy implementation.

What drives the dynamic relationship between sovereign credit default swaps and exchange rates?

What drives the dynamic relationship between sovereign credit default swaps and exchange rates?

Dissecting E, S, and G for risk mitigation: insights from the term structure of CDS

ABSTRACT In this study, we utilize a comprehensive dataset of US-traded credit default swaps (CDS) to assess the impact of environmental, social, and governance (ESG) adoption on firm credit risk. Our study examines corporate bonds with key maturities from 0.5 to 30 years, covering data from 2007 to 2022. We apply fixed effects regression to analyse the impact of ESG scores on CDS spreads. The results are validated through a battery of robustness checks primarily the 2SLS method. The study finds that ESG scores, including the individual pillars, play a significant role in mitigating credit risk. The intriguing aspect of the finding is the decline in risk mitigation as the term-to-maturity increases. Further, the social pillar causes the highest sensitivity to credit risk, followed by the environmental and governance pillars. The effect of ESG adoption is slightly greater for subordinated bonds compared to senior tranches, however, the effects diverge for individual pillars. The study offers practical insights as understanding the relationship between sustainable practices and CDS term structure helps refine investment strategies and specifically pricing of credit risk.

African Sovereign Risk Premia and International Market Assets: A Relook Under The COVID-19 Outbreak

Using the wavelet multiscale coherence technique, the paper examines the interdependences between global market assets, sovereign credit default swap (CDS) and yield-to-maturity on bond spread for African economies from January 2019 to March 2023. The empirical results primarily reveal a high level of coherence between global market assets and Africa’s sovereign CDS and yield-to-maturity, although varying across countries and time-frequency domain. Notably, the high degree of coherence and the positive co-movement between sovereign CDS and global market assets are more concentrated at the medium and upper frequency bands. The observed intensity of co-movements between global market assets and sovereign CDS/yield-to-maturity (YTM) of bond spread, with global market assets broadly serving as leading variables, suggests that an increased global investor’s risk aversion positively affects the yields on Africa market bonds. Among the global market assets, we identified that VIX (which is implied volatility of S&P500) has the dominant influence on Africa sovereign CDS/YTM compared to that emanating from Bitcoin and Godman Sachs Commodity Index. This is highly conceivable as VIX gauges bubbling global risks and uncertainties which considerably influences investor’s risk aversion. The heterogeneous lead/lag dynamics also provide useful information to global investors, including by utilizing African markets to rebalance their portfolios for risk management purposes. The empirical findings thus provide further critical information to investors for hedging purposes, and to policymakers in formulating sovereign risk management policies oriented towards minimizing sovereign default risks.

The Application of Calculus in Credit Default Swaps: Pricing, Risk Assessment, and Market Implications

This paper aims at the investigation of one of the derivatives, namely from the group of Credit Default Swaps, with the help of calculus and, more particularly, differential equations and integrals. The plan is to show how these calculative instruments may be utilized to price and risk measure CDS and to thereby illustrate the utility of such models in mitigating financial risks. The paper is structured as follows: In Section 2, ‘The mechanics and functionality of CDS’, the focus is brought on the specifics of construction of CDS contracts, and the matter of their pricing. Valuation of CDS is described in section three where differential equations and integrals are used in the mathematical modeling of these instruments. Section 4 also focuses on the connection between CDS and market stability; this section also looks at the positive and negative effects of CDS on the financial markets. Finally, Section 5 provides conclusion and recommendation for the subsequent research.

Sovereign CDS Spread and Term Structure Forecasting Based on Neural Network

The article aims to forecast credit risk for BRICS countries using daily credit default swaps (CDS) spreads obtained from Datastream data base from 2018 to 2023. Our approach consists, first, of forecasting the CDS spread in order to estimate the forecasted CDS term structure. The general regression neural network (GRNN) is used to predict the CDS spread. By checking the accuracy of the prediction, the results show that the GRNN model can be recommended as an effective forecasting tool for CDS spread. Second, the predicted spreads are used to estimate the forecasted CDS term structure using the Nelson–Siegel model. The results show that for Russia, overall, the CDS spreads in the long term are less than those in the short term, which implies that the future outlook is more optimistic, given the events that occurred during the study period, but it still retains the highest level of credit risk compared to other countries. Unlike Brazil, India and South Africa, the future outlook is more pessimistic. For China, the term structure is unstable; in the short term, there is a tendency to reduce the risk, but for longer horizons, the risk will increase. Thus, BRICS countries have different risk profiles depending on investment horizons. The study’s findings help policymakers in developing tailored risk management strategies for BRICS countries and guide investors in making informed credit investment decisions. The use of advanced forecasting tools like GRNN and Nelson–Siegel models emphasizes the importance of sophisticated techniques in enhancing financial market resilience.

Matrix GARCH model: Inference and application*

Matrix-variate time series data are largely available in applications. However, no attempt has been made to study their conditional heteroskedasticity that is often observed in economic and financial data. To address this gap, we propose a novel matrix generalized autoregressive conditional heteroskedasticity (GARCH) model to capture the dynamics of conditional row and column covariance matrices of matrix time series. The key innovation of the matrix GARCH model is the use of a univariate GARCH specification for the trace of conditional row or column covariance matrix, which allows for the model identification. Moreover, we introduce a quasi-maximum likelihood estimator (QMLE) for model estimation and develop a portmanteau test for model diagnostic checking. Simulation studies are conducted to assess the finite-sample performance of the QMLE and portmanteau test. To handle large dimensional matrix time series, we also propose a matrix factor GARCH model, and establish its theoretical properties. Finally, we demonstrate the superiority of the matrix GARCH and matrix factor GARCH models over existing multivariate GARCH-type models in volatility forecasting and portfolio allocations using three applications on credit default swap prices, global stock sector indices, and future prices.

Practical Applications of Is Bloomberg’s Credit Default Swaps Model Superior in Predicting Defaults?

Practical Applications of Is Bloomberg’s Credit Default Swaps Model Superior in Predicting Defaults?

Does Bitcoin Hedge Industry Credit Risk? A Comparison with Gold

Credit default swaps are considered indicators of default probability and used to measure credit risk in different sectors of the US industry. This study examines the effectiveness of hedging and safehaven options for US sectoral credit default swap indices, focusing on whether Bitcoin or gold can serve as effective assets for mitigating credit risk in US industries. The GARCH model with dummy variables and quantile regression are employed to estimate the hedging and safe-haven properties of Bitcoin and gold. The findings indicate that both Bitcoin and gold can be utilized as effective hedging and safe haven assets for US industry credit risk. Furthermore, the study highlights the superior hedging potential and safe-haven properties of Bitcoin compared to gold. Overall, the results suggest that investors and portfolio managers can effectively utilize Bitcoin and gold to protect against credit risk in different US sectors, regardless of market and economic conditions.

The Causality Relationship between Credit Default Swaps (CDS) and Portfolio Investments: The Case of Türkiye

This study examines the causality relationship between portfolio investments and credit default swaps (CDS) in Türkiye. Analysing the dynamics between portfolio investments and CDS premiums, two important variables for financial markets is critical to understanding how risk perception and investment decisions are affected. While portfolio investments are generally considered an indicator of the confidence of foreign investors in the country's economy, CDS premiums are an important risk measure that reflects the country's debt risk and the risk perception of market participants. In this context, examining the relationships between the two variables contributes to the understanding of the effects of investor behavior and risk perception on macroeconomic indicators in financial markets. In the study, the Granger causality test was applied using data from the period 2014Q1-2024Q1. The results obtained show that CDS premiums have a significant and unidirectional causal effect on portfolio investments. Increases in CDS premiums increase investors' risk perception and lead to a decrease in portfolio investments. On the other hand, no causal effect of portfolio investments on CDS premiums was found. These findings emphasize the importance of risk management in terms of portfolio investments in Türkiye and reveal that CDS premiums play a role in investor decisions.

Volatility feedback and dealership position: Evidence from the CDS Index, Corporate Bonds, and Government Bonds

Our study comprehensively confirms the existence of the volatility feedback effect for corporate bonds and the Credit Default Swap (CDS) indexes. We also find that dealers’ net protection-buying position of the CDS indexes relates to high credit spreads for the CDS indexes and the representative corporate bonds, and this relationship is associated with dealers’ compensation. This study is a pioneer in investigating CDS index swaptions and finding an implied volatility smirk and that hedging activities of dealers’ net positions of the underlying CDS index relate to the swaption premiums.

ЗАДАЧА ОПТИМАЛЬНОГО СТОХАСТИЧЕСКОГО УПРАВЛЕНИЯ И ОЦЕНКИ СТОИМОСТИ КОРПОРАТИВНЫХ ОБЛИГАЦИЙ, ЗАВИСЯЩИХ ОТ ВРЕМЕНИ И СЛУЧАЙНЫХ СОСТОЯНИЙ ПАРАМЕТРОВ

In the optimal stochastic control problem, one estimates, using the utility indifference method, the bond price and the premium of a default swap contract (Credit default swap) when the model parameters (market interest rate, drift coef-ficient, and volatility of risky underlying assets) are random functions of time and state. Namely, the interest rate of the risk-free asset depends on time, and the prices of risky assets are described by linear homogeneous stochastic dif-ferential equations (SDEs) with multiplicative noise. To do this, the authors consider a portfolio with a risk-free asset and a risky asset with no default risk. For each such portfolio, the authors determine the amount of risky assets that maximizes the expected utility of its final wealth. This quantity allows one to solve the parabolic partial differential equations arising from the Hamilton-Jacobi-Bellman (HJB) equation by transforming them into ordinary differential equations using the method of variable separation to obtain the instantaneous value function of each portfolio. The authors derive the bond price and the default swap-contract premium (CDS) rate, which are the amounts that provide the same level of the expected utility by investing all of one’s wealth in a portfolio that does not contain these credit instruments, or by investing these amounts in credit instruments and the remainder of one’s wealth in the portfolio.

Structured factor copulas for modeling the systemic risk of European and United States banks

In this paper, we employ Credit Default Swaps (CDS) to model the joint and conditional distress probabilities of banks in Europe and the U.S. using factor copulas. We propose multi-factor, structured factor, and factor-vine models where the banks in the sample are clustered according to their geographic location. We find that within each region, the co-dependence between banks is best described using both, systematic and idiosyncratic, financial contagion channels. However, if we consider the banking system as a whole, then the systematic contagion channel prevails, meaning that the distress probabilities are driven by a latent global factor and region-specific factors. In all cases, the co-dependence structure of bank CDS spreads is highly correlated in the tail. The out-of-sample forecasts of several measures of systemic risk allow us to identify the periods of distress in the banking sector over the recent years including the COVID-19 pandemic, the interest rate hikes in 2022, and the banking crisis in 2023.

Cost of Capital in the Energy Sector, in Emerging Markets, the Case of a Dollarized Economy

This article estimates the weighted average cost of capital (WACC) for the energy sector in Ecuador, a country with a dollarized economy and illiquid stock markets. Thus, reference companies in the region were taken, and at the same time combined with characteristics of national companies, establishing a useful methodology, which makes sense with the acceptable discount rates in the Ecuadorian economy. For the above, four estimation alternatives were used. In method one, the traditional WACC formula was applied using interest rates and risk premiums from the U.S. market, which resulted in an overestimation due to the double penalty of the country risk and the U.S. market premium. Method two adjusted the market risk premium to consider only the Ecuador-specific risk premium, thus avoiding the double penalty. In method three, the credit default swap (CDS) was used to calculate the country risk premium, and the CDS was excluded from the nominal interest rate, avoiding redundancies. Finally, method four combined the U.S. interest rate with the CDS directly to calculate the market risk premium, more accurately reflecting local economic conditions in a dollarized economy. The WACC results range from 12.63% to 29.70%. In addition, a dummy variable was controlled for during the pandemic period. This article highlights the need for methodologies adapted to emerging markets, since traditional approaches would overestimate the WACC.

Assessing the sovereign-bank interdependence in Eurozone core countries

PurposeThe aim of this study is to determine whether financial contagion is transmitted through macroeconomic fundamentals, not only in weaker countries but also in strong European Monetary Union (EMU) economies.Design/methodology/approachThis study conducts, for the first time, an analysis of the spillover effects resulting from a shock to Italian sovereign risk on the banking systems and credit default swaps (CDS) of five EMU core countries during the period 2012–2018, employing a global vector autoregressive (GVAR) approach. Spatial interdependence is quantified through the cross-country distance in the deficit-to-gross domestic product (GDP) ratio.FindingsThe findings reveal the existence of both a “doom-loop” between banks and sovereign bonds and a “bad neighbours” effect. The susceptibility to spillovers is notably higher in economies displaying a larger deficit-to-GDP ratio. These results suggest that differences in fiscal fundamentals could drive financial contagion even within core countries, indicating a need for evaluating the stability of the entire EMU system.Originality/valueUnlike previous studies, we utilize the cross-country distance in the deficit-to-GDP ratio as a measure of fiscal fundamentals distance for the countries under investigation. To the best of our knowledge, our study is the first to analyse this matter in EMU core countries using a GVAR methodology.

Assessing the Pandemic Aviation Crisis: Speculative Behavior, Government Bail Outs, and Accommodative Monetary Policy

The COVID-19 pandemic was a health, economic, and financial crisis. The aviation sector was one of the most severely hit. Despite the extensive literature on this, COVID-Finance has been focused on stock returns, neglecting what could be learnt from the spreads of airlines’ credit default swaps (CDSs). This would seem of the utmost importance, given the epicenter of the crisis within the credit market. In this paper, an in-depth analysis of airlines’ CDS spreads is conducted. It is found that they were severely hit, for all airlines studied. However, the results of the PSY test showed that speculative trading led the surge, as explosive roots were found in the spreads of all these aviation firms. The dramatic increase in CDS spreads has contributed to already high borrowing costs for airlines. Our results suggest that aviation bail outs have helped to mitigate spreads’ explosiveness. Monetary policy measures have also limited, albeit indirectly, the funding risk posed by the government bail outs. By the end of March 2021, spreads were no longer explosive, and were approaching, at highly heterogeneous paces, their pre-pandemic values. Notwithstanding, airlines’ stock prices have been notably resistant to recovery.

Time-varying co-movement of sovereign credit default swaps markets: Evidence from Asia-Pacific countries

This study explores the drivers of the co-movement of major sovereign credit default swaps (CDS) markets in Asia-Pacific countries. The lower differentials in fiscal performance among the sample countries contribute to an increase in the co-movement of the CDS markets. The political clearance differentials of corruption control among the sample countries turned out to have a negative relationship with the market co-movement. A higher similarity of social labor risk among the sample countries is positively associated with the co-movement of the CDS markets.

The importance of green patents for CDS pricing: The role of environmental disclosures

Corporate green innovation to address global climate change has potential spillover effects through positive financial outcomes. This study examines how the credit market takes green innovation, measured by the approval of green patents, into account to determine the credit default swap (CDS) premia. Using a sample of United States (US) firms from 2002 to 2020, this research finds that the CDS market favourably prices green innovation: firms with more green patents have lower CDS spread, suggesting that the CDS market considers firms' green innovation in their investment decision. While greater firm-provided environmental disclosures boost the effect of green innovation, involuntary environmental exposures by external channels such as print and online media offset the favourable effect of green innovation on CDS spread. The green technology pilot program by the US Patent and Trademark Office in 2009 is exploited as a quasi-natural experimental setting to apply a difference-in-differences analysis, confirming the favourable effect of green innovation on CDS spread. The results remain robust to various sensitivity and other endogeneity tests. Managers intending to reconcile green innovation with their stakeholder value maximisation objective may find the findings interesting.

Public's evaluation of ESG and credit default swap: Evidence from East Asian countries

We investigate whether investors' sentiment on environmental, social, and governance (ESG) factors negatively affects a firm's spread for credit default swaps (CDS) in East Asian countries. We use the Kyoto Protocol as an exogenous shock to public sentiment on ESG and observe that it strengthens the negative influence of that sentiment on CDS spreads. Furthermore, we find consistent results on the discrepancy in CDS spreads between firms and their respective countries, as well as the term structure of the spreads. Our findings demonstrate that the public's perception of ESG can reduce investors' concerns about firms' credit risk.

Voluntary forward-looking disclosures and default risk pricing

This study examines the effects of textual and numerical information contained in voluntary forward-looking management forecast reports (MFRs) on the pricing of default risk. We find that abnormal changes in credit default swap (CDS) premiums around MFR issuance dates are inversely associated with textual quality and the extent of positive textual news conveyed in the MFR. Furthermore, we find that the negative association of CDS premiums with either textual or numerical news is qualified by the MFR’s textual quality. Collectively, our evidence implies that CDS counterparties use textual quality to verify the quality of the information disclosed in both textual and numerical modes before impounding it into the default risk price. These findings suggest that multimodal verification can enhance the overall information quality of incentive-driven disclosures.