The use of credit default swaps by bond mutual funds: Liquidity provision and counterparty risk

Corporate bond mutual funds increased their selling of credit protection in the credit default swaps (CDS) market during the 2007–2008 financial crisis. This trading activity was primarily in multi-name CDS, greater among larger and established funds, and directed toward counterparty dealers in financial distress. Funds that sold credit protection during the crisis experienced greater credit market risk and superior post-crisis performance, consistent with higher expected returns from liquidity provision. Funds using Lehman Brothers as a counterparty experienced abnormal outflows and returns of –2% immediately following Lehman's bankruptcy, suggesting that funds’ opportunistic trading in CDS exposed investors to counterparty risk.     

Laying off credit risk: Loan sales versus credit default swaps

How do markets for debt cash flow rights, with and without accompanying control rights, affect the efficiency of lending? A bank makes a loan, learns if it needs monitoring, and then decides whether to lay off credit risk. The bank can transfer credit risk by either selling the loan or buying a credit default swap (CDS). With a CDS, the originating bank retains the loan's control rights; with loan sales, control rights pass to the loan buyer. Credit risk transfer leads to excessive monitoring of riskier credits and insufficient monitoring of safer credits. Increases in banks' cost of equity capital exacerbate these effects. For riskier credits, loan sales typically dominate CDS but not for safer credits. Once repeated lending and consequent reputation concerns are modeled, although CDSs remain dominated by loan sales for riskier credits, for safer credits they can dominate loan sales, supporting better monitoring (albeit to a limited extent) while allowing efficient risk sharing. Restrictions on the bank's ability to sell the loan expand the range in which CDSs are used and monitoring is too low.     

Counterparty credit risk and the credit default swap market

Counterparty credit risk has become one of the highest-profile risks facing participants in the financial markets. Despite this, relatively little is known about how counterparty credit risk is actually priced. We examine this issue using an extensive proprietary data set of contemporaneous CDS transaction prices and quotes by 14 different CDS dealers selling credit protection on the same underlying firm. This unique cross-sectional data set allows us to identify directly how dealers' credit risk affects the prices of these controversial credit derivatives. We find that counterparty credit risk is priced in the CDS market. The magnitude of the effect, however, is vanishingly small and is consistent with a market structure in which participants require collateralization of swap liabilities by counterparties.     

The relationship between liquidity risk and credit risk in banks

This paper investigates the relationship between the two major sources of bank default risk: liquidity risk and credit risk. We use a sample of virtually all US commercial banks during the period 1998–2010 to analyze the relationship between these two risk sources on the bank institutional-level and how this relationship influences banks’ probabilities of default (PD). Our results show that both risk categories do not have an economically meaningful reciprocal contemporaneous or time-lagged relationship. However, they do influence banks’ probability of default. This effect is twofold: whereas both risks separately increase the PD, the influence of their interaction depends on the overall level of bank risk and can either aggravate or mitigate default risk. These results provide new insights into the understanding of bank risk and serve as an underpinning for recent regulatory efforts aimed at strengthening banks (joint) risk management of liquidity and credit risks.     

Exploring the components of credit risk in credit default swaps

In this paper, we test the influence of various fundamental variables on the pricing of credit default swaps. The theoretical determinants that are important for pricing credit default swaps include the risk-free rate, industry sector, credit rating, and liquidity factors. We suggest a linear regression model containing these different variables, especially focusing on liquidity factors. Unlike bond spreads which have been shown to be inversely related to liquidity (i.e., the greater the liquidity, the lower the spread), there is no a priori reason that the credit default swap spread should exhibit the same relationship. This is due to the economic characteristics of a credit default swap compared to a bond. Our empirical result shows that all the fundamental variables investigated have a significant effect on the credit default swap spread. Moreover, our findings suggest that credit default swaps that trade with greater liquidity have a wider credit default swap spread.     

Transitional credit modelling and its relationship to market value at risk: an Australian sectoral perspective

Internal credit risk modelling is important for banks for the calculation of capital adequacy in terms of the Basel Accords, and for the management of sectoral exposure. We examine Credit Value at Risk (VaR), Conditional Credit Value at Risk (Credit CVaR) and the relationship between market and credit risk. Significant association is found between different Credit CVaR methods, and between market and credit risk. Simpler Credit CVaR methods are found to be viable alternatives to more complex methodology. The relationship between market and credit risk is used to develop a new model that allows banks to incorporate industry risk into transition modelling, without macroeconomic analysis.     

Bank use of sovereign CDS in the Eurozone crisis: Hedging and risk incentives

Using a comprehensive dataset from German banks, we document the usage of sovereign credit default swaps (CDS) during the European sovereign debt crisis of 2008–2013. Banks used the sovereign CDS market to extend, rather than hedge, their long exposures to sovereign risk during this period. Lower loan exposure to sovereign risk is associated with greater protection selling in CDS, the effect being weaker when sovereign risk is high. Bank and country risk variables are mostly not associated with protection selling. The findings are driven by the actions of a few non-dealer banks which sold CDS protection aggressively at the onset of the crisis, but started covering their positions at its height while simultaneously shifting their assets towards sovereign bonds and loans. Our findings underscore the importance of accounting for derivatives exposure in building a complete picture and understanding fully the economic drivers of the bank-sovereign nexus of risk.     

Portfolio frontiers with restrictions to tracking error volatility and value at risk

Asset managers are often given the task of restricting their activity by keeping both the value at risk (VaR) and the tracking error volatility (TEV) under control. However, these constraints may be impossible to satisfy simultaneously because VaR is independent of the benchmark portfolio. The management of these restrictions is likely to affect portfolio performance and produces a wide variety of scenarios in the risk-return space. The aim of this paper is to analyse various interactions between portfolio frontiers when risk managers impose joint restrictions upon TEV and VaR. Specifically, we provide analytical solutions for all the intersections and we propose simple numerical methods when such solutions are not available. Finally, we introduce a new portfolio frontier.     

CDS as insurance: Leaky lifeboats in stormy seas

What market features of financial risk transfer exacerbate counterparty risk? To analyze this, we formulate a model which elucidates important differences between financial risk transfer and traditional insurance, using the example of Credit Default Swaps (CDS). We allow for (heterogeneous) insurer insolvency, which captures the possibility that relatively risky counterparties may exist in the market. Further, we find that stable insurers become less stable as the price of the contract decreases. The analysis includes insured parties that have heterogeneous motivations for purchasing CDS. For example, some may own the underlying asset and purchase CDS for risk management, while others buy these contracts purely for trading purposes. We show that traders will choose to contract with less stable insurers, resulting in higher counterparty risk in this market relative to that of traditional insurance; however, a regulatory policy that removes traders can, perversely, cause stable counterparties to become less stable. We conclude with two extensions of the model that consider a Central Counterparty (CCP) arrangement and the consequences of asymmetric information over insurer type.     

The valuation of a firm’s investment opportunities: a reduced form credit risk perspective

This paper develops a valuation model for a firm’s investment opportunities. Given standard market imperfections, we show that maximizing the firm’s equity value is consistent with the need to include a capital charge for an investment specific to a firm’s capital structure and in excess of the investment’s market determined risk. A reduced form credit risk perspective is taken to enable a continuous time implementation. This continuous time implementation is illustrated within the paper.      

Haar wavelets-based approach for quantifying credit portfolio losses

This paper proposes a new methodology to compute Value at Risk (VaR) for quantifying losses in credit portfolios. We approximate the cumulative distribution of the loss function by a finite combination of Haar wavelet basis functions and calculate the coefficients of the approximation by inverting its Laplace transform. The Wavelet Approximation (WA) method is particularly suitable for non-smooth distributions, often arising in small or concentrated portfolios, when the hypothesis of the Basel II formulas are violated. To test the methodology we consider the Vasicek one-factor portfolio credit loss model as our model framework. WA is an accurate, robust and fast method, allowing the estimation of the VaR much more quickly than with a Monte Carlo (MC) method at the same level of accuracy and reliability.     

Seeking causality between liquidity risk and credit risk: TED-OIS spreads and CDS indexes

Since the Global Financial Crisis, credit risk and its management have become one of the most appealing topics in finance literature. In this study, we investigate the interaction of credit risk and liquidity risk through the TED and the OIS spreads and various credit default swap indexes from the CDX and the iTraxx family (CDXIG, CDXHY, ITEEU, and ITEXO). The empirical analysis is conducted through the Kapetanios unit root test, the EGARCH model, the Bootstrap Toda-Yamamoto modified Wald test and the asymmetric causality analysis. The results of symmetric and asymmetric causality methods reveal that liquidity risk appears to play an important role in credit risk, and in most cases, the TED and the OIS spreads dominate the CDS indexes. It can, thus, be concluded that the TED and the OIS spreads are superior to the CDS indexes as an early warning indicator in the credit market.     

Impact of multiple curve dynamics in credit valuation adjustments under collateralization

We present a detailed analysis of interest rate derivatives valuation under credit risk and collateral modeling. We show how the credit and collateral extended valuation framework presented in Pallavicini et al. [Funding valuation adjustment: FVA consistent with CVA, DVA, WWR, collateral, netting and re-hyphotecation, 2011], and the related collateralized valuation measure, can be helpful in defining the key market rates underlying the multiple interest rate curves that characterize current interest rate markets. A key point is that spot Libor rates are to be treated as market primitives rather than being defined by no-arbitrage relationships. We formulate a consistent realistic dynamics for the different rates emerging from our analysis and compare the resulting model performances to simpler models used in the industry. We include the often neglected margin period of risk, showing how this feature may increase the impact of different rates dynamics on valuation. We point out limitations of multiple curve models with deterministic basis considering valuation of particularly sensitive products such as basis swaps. We stress that a proper wrong way risk analysis for such products requires a model with a stochastic basis and we show numerical results confirming this fact.     

Liquidity,liquidity risk,and information flow: Lessons from an emerging market

This paper examines the role of public and private information flows in intraday liquidity and intraday liquidity risk in the Tunisian stock market. Our empirical results are based on ARMA and GARCH-type models and show that, for major Tunisian stocks, gradually elapsed public information together with gradually elapsed private information in the market is the dominant factor in liquidity improvements in the Tunisian stock market. Liquidity improvements are generated by a decrease in the bid-ask spread accompanied by an increase in the depth at best limit. Our results clearly indicate that the arrival of public information in a sequential manner is the dominant factor generating increases in liquidity risk related to the bid-ask spread, while the advent of private information in a contemporaneous manner is the dominant factor generating increases in liquidity risk related to the depth at best limit. Additionally, our results show that liquidity risk persistence disappears when trading volume and order imbalance are included as explanatory variables in the conditional variance equation.     

Interpretable selective learning in credit risk

Forecasting credit default risk has been an important research field for several decades. Traditionally, logistic regression has been widely recognized as a solution because of its accuracy and interpretability. Although complex machine learning models may improve accuracy over simple logistic regressions, their interpretability has prevented their use in credit risk assessment. We introduce a neural network with a selective option to increase interpretability by distinguishing whether linear models can explain the dataset. Our methods are tested on two datasets: 25,000 samples from the Taiwan payment system collected in October 2005 and 250,000 samples from the 2011 Kaggle competition. We find that, for most of samples, logistic regression will be sufficient, with reasonable accuracy; meanwhile, for some specific data portions, a shallow neural network model leads to much better accuracy without significantly sacrificing interpretability.     

Tournament incentives and firm credit risk: Evidence from credit default swap referenced firms

In this paper, we evaluate the impact of managerial tournament incentives on firm credit risk in credit default swap (CDS) referenced firms. We find that intra‐firm tournament incentives are negatively related to credit risk. Our results suggest that tournament incentives reduce credit risk by alleviating the potential for underinvestment when managers are concerned about exacting empty creditors. Further, we find that tournament incentives decrease credit risk when internal governance is strong or product market competition is intense. Taken together, our results suggest that creditors perceive senior manager tournament incentives (SMTI) as a critical determinant of a firm's credit risk, particularly in settings where managerial risk aversion is high.     

The effect of corporate diversification on credit risk: new evidence from European credit default swap spreads

This article investigates the impact of corporate diversification on credit risk. To our best knowledge, this is the first paper to use credit default swap (CDS) spreads instead of bond yield or revalued book values to test the risk‐reduction hypothesis. The analysis relies upon a sample of STOXX^® EUROPE 600 index members and covers the years 2010–2014. After controlling for various CDS‐ and firm‐specific variables, we find that diversification strategies do not significantly lower CDS premiums. Multilevel mediation analysis further shows that information asymmetries overcompensate the risk‐reducing effects resulting from corporate diversification.     

The disclosure of risk in financial statements

The accounting information currently issued by firms is not wholly adequate when used for decision making purposes, and within that process, for forecasting, for which additional information on risks is required. Therefore a reform of the current framework becomes necessary. Within this reform an adequate scheme and typology for the risks facing firms must be established and a set of specific risk quantification models must be designed. This paper focuses on both issues, showing all the risks that can affect firms and proposing a quantification model for each one.     

Implied liquidity risk premium in the term structure of sovereign credit default swap and bond spreads

In this study, we focus on the dynamic properties of the risk-neutral liquidity risk premium specific to the sovereign credit default swap (CDS) and bond markets. We show that liquidity risk has a non-trivial role and participates directly to the variation over time of the term structure of sovereign CDS and bond spreads for both the pre- and crisis periods. Secondly, our results indicate that the time-varying bond and CDS liquidity risk premium move in opposite directions which imply that when bond liquidity risk is high, CDS liquidity risk is low (and vice versa), which may in turn be consistent with the substitution effect between CDS and bond markets. Finally, our Granger causality analysis reveals that, although the magnitude of bond and CDS liquidity risk is substantially different, there is a strong liquidity flow between the CDS and the bond markets, however, no market seems to consistently lead the other.