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.     

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.     

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.     

Financial sector strategies and financial sector outcomes: Do the strategies perform?

Financial sector strategies enable financial policymakers and stakeholders to take a holistic view at the financial development needs in their country and to formulate balanced financial policies. They help policymakers consider the systemic risk that different development policies involve and choose an informed way forward. We construct a new dataset of historical financial sector strategies covering 150 countries over the period 1985–2014, and assess the strategies using the rating criteria proposed by Maimbo and Melecky (2014). We then investigate how the quality of the strategies can affect financial sector outcomes such as financial depth, inclusion, efficiency and stability. We find that the use of financial sector strategies helped increase financial sector deepening, inclusion and stability, and that this impact could be greater for higher quality strategies. One way how financial sector strategies can improve financial sector outcomes is by improving the regulatory framework for finance. A significant relationship between the use of strategies and the efficiency of banks is not confirmed.     

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.     

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.     

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.     

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.     

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.     

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.     

Corporate credit risk prediction under stochastic volatility and jumps

This paper examines the impact of allowing for stochastic volatility and jumps (SVJ) in a structural model on corporate credit risk prediction. The results from a simulation study verify the better performance of the SVJ model compared with the commonly used Merton model, and three sources are provided to explain the superiority. The empirical analysis on two real samples further ascertains the importance of recognizing the stochastic volatility and jumps by showing that the SVJ model decreases bias in spread prediction from the Merton model, and better explains the time variation in actual CDS spreads. The improvements are found particularly apparent in small firms or when the market is turbulent such as the recent financial crisis.     

Recovering default risk from CDS spreads with a nonlinear filter

We propose a nonlinear filter to estimate the time-varying default risk from the term structure of credit default swap (CDS) spreads. Based on the numerical solution of the Fokker–Planck equation (FPE) using a meshfree interpolation method, the filter performs a joint estimation of the risk-neutral default intensity and CIR model parameters. As the FPE can account for nonlinear functions and non-Gaussian errors, the proposed framework provides outstanding flexibility and accuracy. We test the nonlinear filter on simulated spreads and apply it to daily CDS data of the Dow Jones Industrial Average component companies from 2005 to 2010 with supportive results.     

Systemic risk in major public contracts

This paper presents a novel approach to the characterisation of “systemic risk” in the context of public sector procurement and contracting. We argue that contemporary risk management practices in project and programme management exhibit a number of limitations. This is particularly relevant to public sector contracting, which, the authors postulate, would benefit from more sophisticated practices that are capable of dealing with risk ‘systemicity’. Drawing on a sample of public sector procurement exercises commissioned by the UK Ministry of Defence (MoD), the paper presents a multi-method approach that aims to increase our understanding of complex outsourcing contracts. The results suggest a need for more appropriate methods of risk analysis, and discuss the practical implications.     

Nowcasting and forecasting global financial sector stress and credit market dislocation

We introduce a new international model for the systematic distress risk of financial institutions from the US, the European Union, and the Asia-Pacific region. Our proposed dynamic factor model can be represented as a nonlinear, non-Gaussian state space model with parameters that we estimate using Monte Carlo maximum likelihood methods. We construct measures of global financial sector risk and of credit market dislocation, where credit market dislocation is defined as a significant and persistent decoupling of the credit risk cycle from macro-financial fundamentals in one or more regions. We show that, in the past, such decoupling has preceded episodes of systemic financial distress. Our new measure provides a risk-based indicator of credit conditions, and as such, complements earlier quantity-based indicators from the literature. In an extensive comparison with such quantity-based systemic risk indicators, we find that the behaviour of the new indicator is competitive with that of the best quantity-based indicators.     

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.     

The conditional dependence structure of insurance sector credit default swap indices

This study assesses the dependence structure of insurance sector credit default swap indices, using a copula-GARCH approach. We use daily data of the US, EU, and UK insurance sectors, covering the period from January 2004 to June 2013. We find substantial increases in dependence during the financial crisis periods. Prior to the crises, various copulas are found to best fit each pair; specifically, asymmetric tail dependence is found for the UK–US pair, suggesting the possibility of large simultaneous losses. However, during the crisis periods, the Frank copula fits best, with no significant tail dependence detected, implying low systemic risks.     

Risk spillover analysis of China’s financial sectors based on a new GARCH copula quantile regression model

This study employs a new GARCH copula quantile regression model to estimate the conditional value at risk for systemic risk spillover analysis. To be specific, thirteen copula quantile regression models are derived to capture the asymmetry and nonlinearity of the tail dependence between financial returns. Using Chinese stock market data over the period from January 2007 to October 2020, this paper investigates the risk spillovers from the banking, securities, and insurance sectors to the entire financial system. The empirical results indicate that (i) three financial sectors contribute significantly to the financial system, and the insurance sector displays the largest risk spillover effects on the financial system, followed by the banking sector and subsequently the securities sector; (ii) the time-varying risk spillovers are much larger during the global financial crisis than during the periods of the banking liquidity crisis, the stock market crash and the COVID-19 pandemic. Our results provide important implications for supervisory authorities and portfolio managers who want to maintain the stability of China’s financial system and optimize investment portfolios.     

The interest rate spreads in the Czech Republic: Different loans,different determinants?

We analyze the determinants of interest rate spreads of different loan categories in the Czech Republic during 2004–2011. We employ a detailed bank supervisory dataset that allows us to construct the actual spreads for four loan categories, namely small and large corporate loans, consumer loans and mortgages, on a monthly basis. Our regression analysis shows that bank and macroeconomic characteristics matter more for setting the spreads for small corporate loans and mortgages rather than for large corporate loans and consumer loans. Interest rate risk determines the spreads for all loan categories. The global financial crisis has, to a certain extent, increased the responsiveness of spreads to interest rate risk and liquidity risk.     

Systemic risk of Chinese financial institutions and asset price bubbles

Although there has not been a large-scale systemic crisis in China, high-risk financial events have occurred continuously in recent years. This research thus creatively analyzes the determinants of systemic risk for Chinese financial institutions from the view of asset price bubbles. First, we identify bubbles in the China stock and real estate markets on the basis of the generalized sup Augmented Dickey-Fuller (GSADF) model and explain the reasons for bubble formations according to the stage of China's economic development and policies implementation. At this stage, considering the differences in economic development levels of different cities, the real estate bubbles in the first, second and third tier cities and the whole country were innovatively identified. Second, on the basis of the DCG-GARCH-CoVaR model to measure the systemic risk of listed financial institutions in China and to classify institutions, the results show that the main source of such risk is the banking sector. Furthermore, by constructing regression models, stock market bubbles and real estate bubbles both positively correlate with systemic risk throughout the sample period. Meanwhile, the impact of bubbles on the systemic risk of different types of financial institutions was taken into account so that regulators prioritized different types of institutions with different characteristics when faced with decisions. Finally, we provide macro-prudential policy advice to regulators in order to weaken the impact of bubbles on financial stability to avoid systemic crises.     

Corporate governance and the insolvency risk of financial institutions

We investigate whether shareholder-friendliness of corporate governance mechanisms is related to the insolvency risk of financial institutions. Using a large sample of U.S. financial institutions over the period 2005–2010, we find that corporate governance is positively related to the insolvency risk of financial institutions as proxied by Merton’s distance to default measure and credit default swap (CDS) spread. We also find that “stronger” corporate governance increases insolvency risk relatively more for larger financial institutions and during the period of the financial crisis. Lastly, our results suggest that shareholder-friendliness of corporate governance mechanisms is viewed unfavorably in the bond market.