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.     

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.     

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.     

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.     

Market perception of sovereign credit risk in the euro area during the financial crisis

We study market perception of sovereign credit risk in the euro area during the financial crisis. In our analysis we use a parsimonious CDS pricing model to estimate the probability of default (PD) and the loss given default (LGD) as perceived by financial markets. In our empirical results the estimated LGDs perceived by financial markets stay comfortably below 40% in most of the samples. Global financial indicators are positively and strongly correlated with the market perception of sovereign credit risk; whilst macroeconomic and institutional developments were at best only weakly correlated with the market perception of sovereign credit risk.     

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.     

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.     

Default models based on scale mixtures of Marshall-Olkin copulas: properties and applications

We present a unification of the Archimedean and the Lévy-frailty copula model for portfolio default models. The new default model exhibits a copula known as scale mixture of Marshall-Olkin copulas and an investigation of the dependence structure reveals that desirable properties of both original models are combined. This allows for a wider range of dependence patterns, while the analytical tractability is retained. Furthermore, simultaneous defaults and default clustering are incorporated. In addition, a hierarchical extension is presented which allows for a heterogeneous dependence structure. Finally, the model is applied to the pricing of CDO contracts. For this purpose, an efficient Laplace transform inversion approach is developed. Supporting a separation of marginal default probabilities and dependence structure, the model can be calibrated to CDS contracts in a first step. In a second step, the calibration of several parametric families to CDO contracts demonstrates a good fitting quality, which further emphasizes the suitability of the approach.     

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.     

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.     

Spillover effects in oil-related CDS markets during and after the sub-prime crisis

This paper investigates the return and volatility spillover effects across oil-related credit default swaps (CDSs), the oil market, and financial market risks for the US during and after the subprime crises. The empirical analysis is based on monthly return and realized volatility data from February 2004 to April 2020. We estimate both static and dynamic generalized dynamic spillover measures based on vector autoregressive (VAR) models. Our full sample empirical findings show that the oil market is the primary source of risk transmission for all the oil-related credit default swaps, while the bond market is the highest source of risk transmission to the stock market and vice versa. We also provide evidence that the regulated monopoly US utility sector has the least role in volatility transmission. Furthermore, the bailout program conducted by the US Treasury and Federal Reserve helped stabilize the US financial market through the purchase of toxic assets after the subprime financial crisis. We find strong evidence that the federal funds rate hike cycles lessen total risk transmission throughout the US bond market. Finally, our findings assert that oil price shocks have a significant effect on the oil-related CDSs in some sub-periods via the demand and supply transmission channels.     

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.     

The impact of EMU on bond yield convergence: Evidence from a time-varying dynamic factor model

This paper examines the dynamics of long term sovereign bond yields for 21 OECD countries. Following Del Negro and Otrok (2008), we estimate a dynamic factor model, with time varying parameters and stochastic volatility, that decomposes the observed variation in bond yields for each country into a common factor, a regional factor (EMU/non-EMU), and an idiosyncratic country specific factor. We find that prior to the financial crisis of 2008, the common factor played a dominant role for most countries in our sample. In the post financial crisis period there is substantial heterogeneity in the relative importance of the EMU and the idiosyncratic factors across different countries. For instance, our results suggest that there was a decoupling between the EMU and bond markets of the periphery economies of Greece, Ireland and Portugal in the post-2008 period. We find that after the onset of sovereign debt crises in these economies, the idiosyncratic factor assumed an important role in driving the bond yield variation. Thereafter, the EMU’s share in bond yield changes in Ireland and Portugal increased considerably since 2012, whereas for Greece the idiosyncratic factor continued to play a significant role in driving bond yields. In contrast, the EMU factor consistently played a dominant role in explaining bond yield changes in Italy and Spain, the other two economies that also experienced severe debt crisis during this period. We argue such differences in the importance of the EMU factor between core and periphery economies can be attributed to the systemic importance of core members for the EMU. This is indicated by our finding that bond yields and credit default swap (CDS) are less sensitive to changes in debt-GDP ratios in countries where the EMU factor played a larger role in the post-2008 period.     

The determinants of corporate bond yields

Previous studies have found that common factors explain a high proportion of corporate bond yields. In this paper, we test whether there is a systematic risk premium beyond that implied by a risk-neutral term structure model. We propose a reduced-form term structure model that incorporates both default and tax effects. After controlling the effects of personal taxes and default risk, empirical tests show that at least two of the Fama–French factors are important for corporate bond yields. Our results suggest that term structure models should incorporate aggregate common risk factors in order to better explain the dynamics of corporate bond yields.     

Robustness of banking networks to idiosyncratic and systemic shocks: a network-based approach

We propose a network-based structural model of credit risk to demonstrate how idiosyncratic and systemic shocks propagate across the banking system and evaluate the costs. The banking system is built as a network of heterogeneous banks which are connected with one another. In such a system, single credit events propagate through the interbank market from debtors to creditors and across the system. The shock is imposed as an unexpected event. We demonstrate that while idiosyncratic shocks cannot substantially disturb the banking system, a systemic shock of even a moderate magnitude can be highly detrimental. Such shock includes a huge contagious potential. We demonstrate that the costs of the shock are largely determined by the extent of contagion and range from negligible to catastrophic. The results imply that a severe crisis has to be initiated by a systemic shock of at least moderate magnitude. Capital ratio and the bank size are two additional factors of the banking system stability. Finally, credit risk analysis is sensitive to the network topology and exhibits a profound nonlinear characteristic.     

Modeling frailty-correlated defaults using many macroeconomic covariates

We propose a novel time series panel data framework for estimating and forecasting time-varying corporate default rates subject to observed and unobserved risk factors. In an empirical application for a U.S. dataset, we find a large and significant role for a dynamic frailty component even after controlling for more than 80% of the variation in more than 100 macro-financial covariates and other standard risk factors. We emphasize the need for a latent component to prevent a downward bias in estimated default rate volatility and in estimated probabilities of extreme default losses on portfolios of U.S. debt. The latent factor does not substitute for a single omitted macroeconomic variable. We argue that it captures different omitted effects at different times. We also provide empirical evidence that default and business cycle conditions partly depend on different processes. In an out-of-sample forecasting study for point-in-time default probabilities, we obtain mean absolute error reductions of more than forty percent when compared to models with observed risk factors only. The forecasts are relatively more accurate when default conditions diverge from aggregate macroeconomic conditions.     

Identifying contagion

Identifying contagion effects during periods of financial crisis is known to be complicated by the changing volatility of asset returns during periods of stress. To untangle this we propose a GARCH (generalized autoregressive conditional heteroskedasticity) common features approach, where systemic risk emerges from a common factor source (or indeed multiple factor sources) with contagion evident through possible changes in the factor loadings relating to the common factor(s). Within a portfolio mimicking factor framework this can be identified using moment conditions. We use this framework to identify contagion in three illustrations involving both single and multiple factor specifications: to the Asian currency markets in 1997–1998, to US sectoral equity indices in 2007–2009 and to the CDS (credit default swap) market during the European sovereign debt crisis of 2010–2013. The results reveal the extent to which contagion effects may be masked by not accounting for the sources of changed volatility apparent in simple measures such as correlation.     

CREDIT DEFAULT SWAPS – WEAPON OF MASS DESTRUCTION OR RELIABLE INDICATOR?

Credit Default Swaps (CDS) are said to increase systemic vulnerability, but they also serve as an ex‐ante indicator of default probabilities, more finely‐tuned and more responsive than ratings agency reports. And they provide a useful mechanism for trading risk and an incentive for good management by businesses and governments.     

Global Credit Risk: World,Country and Industry Factors

We investigate the dynamic properties of systematic default risk conditions for firms in different countries, industries and rating groups. We use a high‐dimensional nonlinear non‐Gaussian state‐space model to estimate common components in corporate defaults in a 41 country samples between 1980:Q1 and s2014:Q4, covering both the global financial crisis and euro area sovereign debt crisis. We find that macro and default‐specific world factors are a primary source of default clustering across countries. Defaults cluster more than what shared exposures to macro factors imply, indicating that other factors also play a significant role. For all firms, deviations of systematic default risk from macro fundamentals are correlated with net tightening bank lending standards, suggesting that bank credit supply and systematic default risk are inversely related. Copyright © 2016 John Wiley & Sons, Ltd.     

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.