Showing papers on "Credit risk published in 2014"
TL;DR: In this paper, the authors identify the effects of monetary policy on credit risk-taking with an exhaustive credit register of loan applications and contracts, and find that a lower overnight interest rate induces lowly capitalized banks to grant more loan applications to ex ante risky firms and to commit larger loan volumes with fewer collateral requirements to these firms, yet with a higher ex post likelihood of default.
Abstract: We identify the effects of monetary policy on credit risk-taking with an exhaustive credit register of loan applications and contracts. We separate the changes in the composition of the supply of credit from the concurrent changes in the volume of supply and quality, and the volume of demand. We employ a two-stage model that analyzes the granting of loan applications in the first stage and loan outcomes for the applications granted in the second stage, and that controls for both observed and unobserved, time-varying, firm and bank heterogeneity through time*firm and time*bank fixed effects. We find that a lower overnight interest rate induces lowly capitalized banks to grant more loan applications to ex ante risky firms and to commit larger loan volumes with fewer collateral requirements to these firms, yet with a higher ex post likelihood of default. A lower long-term interest rate and other relevant macroeconomic variables have no such effects.
965 citations
TL;DR: In this article, the authors show that post-bailout changes in sovereign CDS explain changes in bank CDS even after controlling for aggregate and bank-level determinants of credit spreads.
Abstract: We model a loop between sovereign and bank credit risk. A distressed financial sector induces government bailouts, whose cost increases sovereign credit risk. Increased sovereign credit risk in turn weakens the financial sector by eroding the value of its government guarantees and bond holdings. Using credit default swap (CDS) rates on European sovereigns and banks, we show that bailouts triggered the rise of sovereign credit risk in 2008. We document that post-bailout changes in sovereign CDS explain changes in bank CDS even after controlling for aggregate and bank-level determinants of credit spreads, confirming the sovereign-bank loop.
535 citations
TL;DR: This paper examined the relationship between competition and the absolute level of risk of individual banks and found that greater competition encourages banks to take on more diversified risks, making the banking system less fragile to shocks.
383 citations
TL;DR: In this article, the authors analyzed whether the political connections of listed firms in the United States affect the cost and terms of loan contracts and found that the cost of bank loans is significantly lower for companies that have board members with political ties.
Abstract: This paper analyzes whether the political connections of listed firms in the United States affect the cost and terms of loan contracts. Using a hand-collected data set of the political connections of S&P 500 companies over the 2003-2008 time period, we find that the cost of bank loans is significantly lower for companies that have board members with political ties. We consider two possible explanations for these findings: a Borrower Channel in which lenders charge lower rates because they recognize that connections enhance the borrower's credit worthiness and a Bank Channel in which banks assign greater value to connected loans to enhance their own relationships with key politicians. After employing a series of tests to distinguish between these two channels, we find strong support for the Borrower Channel but no direct evidence supporting the Bank Channel. Finally, we demonstrate that political connections reduce the likelihood of a capital expenditure restriction or liquidity requirement commanded by banks at the origination of the loan. Taken together, our results suggest that political connections increase the value of U.S. companies and reduce monitoring costs and credit risk faced by banks, which, in turn, reduces the borrower's cost of debt.
368 citations
Journal Article•
TL;DR: Eggers as discussed by the authors describes persistent surveillance technologies that score people in every imaginable way, such as high school students' test results, their class rank, their school's relative academic strength, and a number of other factors.
Abstract: [Jennifer is] ranked 1,396 out of 179,827 high school students in Iowa. . . . Jennifer's score is the result of comparing her test results, her class rank, her school's relative academic strength, and a number of other factors. . . .[C]an this be compared against all the other students in the country, and maybe even the world? . . .That's the idea . . . .That sounds very helpful. . . . And would eliminate a lot of doubt and stress out there.-Dave Eggers, The Circle1INTRODUCTION TO THE SCORED SOCIETYIn his novel The Circle, Dave Eggers imagines persistent surveillance technologies that score people in every imaginable way. Employees receive rankings for their participation in social media.2 Retinal apps allow police officers to see career criminals in distinct colors-yellow for low-level offenders, orange for slightly more dangerous, but still nonviolent offenders, and red for the truly violent.3 Intelligence agencies can create a web of all of a suspect's contacts so that criminals' associates are tagged in the same color scheme as the criminals themselves.4Eggers's imagination is not far from current practices. Although predictive algorithms may not yet be ranking high school students nationwide, or tagging criminals' associates with color-coded risk assessments, they are increasingly rating people in countless aspects of their lives.Consider these examples. Job candidates are ranked by what their online activities say about their creativity and leadership.5 Software engineers are assessed for their contributions to open source projects, with points awarded when others use their code.6 Individuals are assessed as likely to vote for a candidate based on their cable-usage patterns.7 Recently released prisoners are scored on their likelihood of recidivism.8How are these scores developed? Predictive algorithms mine personal information to make guesses about individuals' likely actions and risks.9 A person's on- and offline activities are turned into scores that rate them above or below others.10 Private and public entities rely on predictive algorithmic assessments to make important decisions about individuals.11Sometimes, individuals can score the scorers, so to speak. Landlords can report bad tenants to data brokers while tenants can check abusive landlords on sites like ApartmentRatings.com. On sites like Rate My Professors, students can score professors who can respond to critiques via video. In many online communities, commenters can in turn rank the interplay between the rated, the raters, and the raters of the rated, in an effort to make sense of it all (or at least award the most convincing or popular with points or "karma"). 12Although mutual-scoring opportunities among formally equal subjects exist in some communities, the realm of management and business more often features powerful entities who turn individuals into ranked and rated objects.13 While scorers often characterize their work as an oasis of opportunity for the hardworking, the following are examples of ranking systems that are used to individuals' detriment. A credit card company uses behavioral-scoring algorithms to rate consumers' credit risk because they used their cards to pay for marriage counseling, therapy, or tire-repair services.14 Automated systems rank candidates' talents by looking at how others rate their online contributions.15 Threat assessments result in arrests or the inability to fly even though they are based on erroneous information.16 Political activists are designated as "likely" to commit crimes.17And there is far more to come. Algorithmic predictions about health risks, based on information that individuals share with mobile apps about their caloric intake, may soon result in higher insurance premiums.18 Sites soliciting feedback on "bad drivers" may aggregate the information, and could possibly share it with insurance companies who score the risk potential of insured individuals. …
277 citations
TL;DR: The authors investigated the relationship between the two major sources of bank default risk: liquidity risk and credit risk and found that both risk categories do not have an economically meaningful reciprocal contemporaneous or time-lagged relationship.
Abstract: 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 U.S. commercial banks during the period 1998 to 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, as developed by the body of literature on bank stability risk in general and credit and liquidity risk in particular. They also serve as an underpinning for recent regulatory efforts aimed at strengthening banks (joint) risk management of liquidity and credit risks, such as the Basel III and Dodd-Frank frameworks.
208 citations
Book•
19 Dec 2014
TL;DR: In this article, a survey of the literature on credit default swaps (CDS) is presented, with a focus on the role of fundamental credit risk factors, liquidity and counterparty risk.
Abstract: Credit default swaps (CDS) have been growing in importance in the global financial markets. However, their role has been hotly debated, in industry and academia, particularly since the credit crisis of 2007-2009. We review the extant literature on CDS that has accumulated over the past two decades. We divide our survey into seven topics after providing a broad overview in the introduction. The second section traces the historical development of CDS markets and provides an introduction to CDS contract definitions and conventions. The third section discusses the pricing of CDS, from the perspective of no-arbitrage principles, structural, and reduced-form credit risk models. It also summarizes the literature on the determinants of CDS spreads, with a focus on the role of fundamental credit risk factors, liquidity and counterparty risk. The fourth section discusses how the development of the CDS market has affected the characteristics of the bond and equity markets, with an emphasis on market efficiency, price discovery, information flow, and liquidity. Attention is also paid to the CDS-bond basis, the wedge between the pricing of the CDS and its reference bond, and the mispricing between the CDS and the equity market. The fifth section examines the effect of CDS trading on firms' credit and bankruptcy risk, and how it affects corporate financial policy, including bond issuance, capital structure, liquidity management, and corporate governance. The sixth section analyzes how CDS impact the economic incentives of financial intermediaries. The seventh section reviews the growing literature on sovereign CDS and highlights the major differences between the sovereign and corporate CDS markets. In the eight section, we discuss CDS indices, especially the role of synthetic CDS index products backed by residential mortgage-backed securities during the financial crisis.We close with our suggestions for promising future research directions on CDS contracts and markets.
184 citations
TL;DR: In this article, Allen, Brand, Jo Scott, Micah Altman and Marjorie Hlava are trialling digital taxonomies to help researchers to identify their contributions to collaborative projects.
Abstract: Liz Allen, Amy Brand, Jo Scott, Micah Altman and Marjorie Hlava are trialling digital taxonomies to help researchers to identify their contributions to collaborative projects.
183 citations
TL;DR: The authors investigated the relationship between the two major sources of bank default risk: liquidity risk and credit risk and found that both risk categories do not have an economically meaningful reciprocal contemporaneous or time-lagged relationship.
Abstract: 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.
172 citations
TL;DR: In this paper, the authors developed an arbitrage-free valuation framework for bilateral counterparty risk, where collateral is included with possible re-hypothecation and showed that the adjustment is given by the sum of two option payoff terms, where each term depends on the netted exposure, i.e., the difference between the on-default exposure and the pre-default account.
Abstract: We develop an arbitrage-free valuation framework for bilateral counterparty risk, where collateral is included with possible re-hypothecation We show that the adjustment is given by the sum of two option payo terms, where each term depends on the netted exposure, ie the dierence between the on-default exposure and the pre-default collateral account We then specialize our analysis to Credit Default Swaps (CDS) as underlying portfolios, and construct a numerical scheme to evaluate the adjustment under a doubly stochastic default framework In particular, we show that for CDS contracts a perfect collateralization cannot be achieved, even under continuous collateralization, if the reference entity’s and counterparty’s default times are dependent The impact of re-hypothecation, collateral margining frequency, and default correlation induced contagion is illustrated with numerical examples
170 citations
TL;DR: In this paper, the authors investigate how the introduction of complex, model-based capital regulation affected credit risk of financial institutions and show that the internal risk estimates employed for regulatory purposes systematically underpredict actual default rates by 5 to 1 percentage points.
Abstract: In this paper, we investigate how the introduction of complex, model-based capital regulation affected credit risk of financial institutions Model-based regulation was meant to enhance the stability of the financial sector by making capital charges more sensitive to risk Exploiting the staggered introduction of the model-based approach in Germany and the richness of our loan-level data set, we show that (1) internal risk estimates employed for regulatory purposes systematically underpredict actual default rates by 05 to 1 percentage points; (2) both default rates and loss rates are higher for loans that were originated under the model-based approach, while corresponding risk-weights are significantly lower; and (3) interest rates are higher for loans originated under the model-based approach, suggesting that banks were aware of the higher risk associated with these loans and priced them accordingly Further, we document that large banks benefited from the reform as they experienced a reduction in capital charges and consequently expanded their lending at the expense of smaller banks that did not introduce the model-based approach Counter to the stated objectives, the introduction of complex regulation adversely affected the credit risk of financial institutions Overall, our results highlight the pitfalls of complex regulation and suggest that simpler rules may increase the efficacy of financial regulation
Posted Content•
TL;DR: In this paper, the authors present new evidence on the structure of interbank connections in key markets: derivatives, marketable securities, repo, unsecured lending and secured lending.
Abstract: We present new evidence on the structure of interbank connections in key markets: derivatives, marketable securities, repo, unsecured lending and secured lending. Taken together, these markets comprise two networks: a network of interbank exposures and a network of interbank funding. Network structure varies across and within these two networks, for reasons related to markets’ different economic functions. Credit risk and liquidity risk therefore propagate in the interbank system through different network structures, with implications for financial stability.
TL;DR: This paper used credit default swaps (CDS) trading data to demonstrate that the credit risk of reference firms, reflected in rating downgrades and bankruptcies, increases significantly upon the inception of CDS trading.
Abstract: We use credit default swaps (CDS) trading data to demonstrate that the credit risk of reference firms, reflected in rating downgrades and bankruptcies, increases significantly upon the inception of CDS trading, a finding that is robust after controlling for the endogeneity of CDS trading. Additionally, distressed firms are more likely to file for bankruptcy if they are linked to CDS trading. Furthermore, firms with more “no restructuring” contracts than other types of CDS contracts (i.e., contracts that include restructuring) are more adversely affected by CDS trading, and the number of creditors increases after CDS trading begins, exacerbating creditor coordination failure in the resolution of financial distress.
Posted Content•
TL;DR: In this paper, the average spreads on the yield of euro area private sector bonds relative to the yield on German federal government securities of matched maturities were constructed at the country level for Germany, France, Italy and Spain.
Abstract: We construct credit risk indicators for euro area banks and non-financial corporations. These are the average spreads on the yield of euro area private sector bonds relative to the yield on German federal government securities of matched maturities. The indicators are also constructed at the country level for Germany, France, Italy and Spain. These indicators reveal that the financial crisis of 2008 has dramatically increased the cost of market funding for both banks and non-financial firms. In contrast, the prior recession following the 2000 U.S. dot-com bust led to widening credit spreads of non-financial firms but had no effect on the credit spreads of financial firms. The 2008 financial crisis also led to a systematic divergence in credit spreads for financial firms across national boundaries. This divergence in cross-country credit risk increased further as the European debt crisis has unfolded since 2010. Since that time, credit spreads for both non-financial and financial firms increasingly reflect national rather than euro area financial conditions. Consistent with this view, credit spreads provide substantial predictive content for a variety of real activity and lending measures for the euro area as a whole and for individual countries. VAR analysis implies that disruptions in corporate credit markets lead to sizeable contractions in output, increases in unemployment, and declines in inflation across the euro area.
TL;DR: In this article, the authors exploit highly disaggregated bank-firm data to investigate the dynamics of foreign vs domestic credit supply in Italy around the period of the Lehman collapse, which brought a sudden and unexpected deterioration of economic conditions and a sharp increase in credit risk.
TL;DR: This paper examined the effect of government guarantees on bank risk taking, using a large data set of matched bank/borrower information, and showed that the effect is larger for banks that ex ante benefitted more from the guarantee.
Abstract: In 2001, government guarantees for savings banks in Germany were removed following a law suit. We use this natural experiment to examine the effect of government guarantees on bank risk taking, using a large data set of matched bank/borrower information. The results suggest that banks whose government guarantee was removed reduced credit risk by cutting off the riskiest borrowers from credit. At the same time, the banks also increased interest rates on their remaining borrowers. The effects are economically large: the Z-Score of average borrowers increased by 7% and the average loan size declined by 13%. Remaining borrowers paid 57 basis points higher interest rates, despite their higher quality. Using a difference-in-differences approach we show that the effect is larger for banks that ex ante benefitted more from the guarantee. We show that both the credit quality of new customers improved (screening) and that the loans of existing riskier borrowers were less likely to be renewed (monitoring), after the removal of public guarantees. Public guarantees seem to be associated with substantial moral hazard effects.
TL;DR: In this paper, the authors evaluated the credit risk of 156 conventional banks and 37 Islamic banks across 13 countries between 2000 and 2012 using Merton's distance-to-default (DD) model, a market-based credit risk measure.
Abstract: This study considers whether Islamic banks and conventional banks have different levels of credit risk. One problem with existing research in this area is the dominance of accounting information to assess credit risk, and this could be especially misleading in the case of Islamic banking. Using Merton’s distance-to-default (DD) model, a market-based credit risk measure, we evaluate the credit risk of 156 conventional banks and 37 Islamic banks across 13 countries between 2000 and 2012. We also calculate the accounting information-based Z-score and nonperforming loan (NPL) ratio for the purpose of comparison. Our results show that Islamic banks have significantly lower credit risk than conventional banks when measuring credit risk with the DD. In contrast, and as expected, Islamic banks exhibit much higher credit risk using the Z-score and NPL ratio. Overall, the findings suggest that the methodology used plays a significant role in assessing the apparent credit risk of Islamic banks.
TL;DR: This paper explored the link between a firm's stock returns and credit risk using a simple insight from structural models following Merton (1974): risk premia on equity and credit instruments are related because all claims on assets must earn the same compensation per unit of risk.
Abstract: We explore the link between a firm's stock returns and credit risk using a simple insight from structural models following Merton (1974): risk premia on equity and credit instruments are related because all claims on assets must earn the same compensation per unit of risk. Consistent with theory, we find that firms' stock returns increase with credit risk premia estimated from CDS spreads. Credit risk premia contain information not captured by physical or risk-neutral default probabilities alone. This sheds new light on the �distress puzzle��the lack of a positive relation between equity returns and default probabilities�reported in previous studies.
TL;DR: In this article, the authors examined how the information quality of ratings from an issuer-paid rating agency (Standard and Poor's) responds to the entry of an investor paid rating agency, the Egan-Jones Rating Company (EJR), by comparing S&P's ratings quality before and after EJR initiates coverage of each firm.
TL;DR: The results show that the proposed profit-based classification measure outperforms the alternative approaches in terms of both accuracy and monetary value in the test set, and that it facilitates model deployment.
TL;DR: In this article, a simple model of sovereign risk in which debt can be traded in secondary markets is proposed, which has two key ingredients: creditor discrimination and private debt reallocation.
TL;DR: In this article, the authors develop a model of the financial sector in which endogenous intermediation among debt financed banks generates excessive systemic risk, and show that a core-periphery network emerges in their model.
Abstract: I develop a model of the financial sector in which endogenous intermediation among debt financed banks generates excessive systemic risk. Financial institutions have incentives to capture intermediation spreads through strategic borrowing and lending decisions. By doing so, they tilt the division of surplus along an intermediation chain in their favor, while at the same time reducing aggregate surplus. I show that a core-periphery network – few highly interconnected and many sparsely connected banks – endogenously emerges in my model. The network is inefficient relative to a constrained efficient benchmark since banks who make risky investments "overconnect", exposing themselves to excessive counterparty risk, while banks who mainly provide funding end up with too few connections. The predictions of the model are consistent with empirical evidence in the literature.
TL;DR: In this article, the authors present new evidence on the structure of interbank connections across key markets: derivatives, marketable securities, repo, unsecured lending and secured lending.
Abstract: We present new evidence on the structure of interbank connections across key markets: derivatives, marketable securities, repo, unsecured lending and secured lending. Taken together, these markets comprise two networks: a network of interbank exposures and a network of interbank funding. Network structure varies across and within these two networks, for reasons related to markets’ different economic functions. Credit risk and liquidity risk therefore propagate in the interbank system through different network structures. We discuss the implications for financial stability.
TL;DR: This paper proposed an empirical framework to assess the likelihood of joint and conditional sovereign default from observed CDS prices, based on a dynamic skewed-t distribution that captures all salient features of the data, including skewed and heavy-tailed changes in the price of CDS protection against sovereign default, and dynamic volatilities and correlations that ensure that uncertainty and risk dependence can increase in times of stress.
Abstract: We propose an empirical framework to assess the likelihood of joint and conditional sovereign default from observed CDS prices. Our model is based on a dynamic skewed-t distribution that captures all salient features of the data, including skewed and heavy-tailed changes in the price of CDS protection against sovereign default, as well as dynamic volatilities and correlations that ensure that uncertainty and risk dependence can increase in times of stress. We apply the framework to euro area sovereign CDS spreads during the euro area debt crisis. Our results reveal significant time-variation in distress dependence and spill-over effects for sovereign default risk. We investigate market perceptions of joint and conditional sovereign risk around announcements of Eurosystem asset purchases programs, and document a strong impact on joint risk.
TL;DR: In this article, the authors study financial markets where agents share risks, but have incentives to default and their financial positions might not be transparent, that is, might not always be mutually observable.
TL;DR: In this article, the authors used a dataset of financial statements that are adjusted by Moody's for its credit analysis, and they found extensive and large differences between firms' reported U.S. GAAP numbers and firms' adjusted numbers.
Abstract: Using a dataset of financial statements that are adjusted by Moody's for its credit analysis, I document extensive and large differences between firms' reported U.S. GAAP numbers and firms' adjusted numbers. Off-balance sheet financing accounts for the largest difference. The adjusted leverage ratio exceeds the reported leverage ratio by 20% (70%) for the median (average) firm. Adjusted profitability ratios and cash flow to debt ratios differ from their U.S. GAAP equivalents primarily because of greater adjusted interest expense and greater adjusted debt numbers. This implies that essentially all firms in the sample understate their leverage. In addition to adjusting reported accounting numbers, credit analysts adjust ratings down by an average of 0.38 notches due to credit risk from qualitative factors. I predict and find that rating agency adjustments are associated with greater credit spreads and a flatter credit spread term structure. This implies that credit ratings are a function of quantitative adjustments to U.S. GAAP numbers and the rating agency's qualitative assessment of credit risk arising from soft factors. The results suggest that rating agency's quantitative and soft adjustments capture true default risk and rating agencies efficiently process accounting and soft information. Thus ratings can serve as a contracting device to incorporate off-balance-sheet debt adjustments and credit-risk increasing soft factors.
TL;DR: In this paper, a modified quantity discount based on both order quantity and advance payment is proposed to coordinate supply chain in a retailer-manufacturer system, where the manufacturer offers quantity discount if the retailer pays part of the payment in advance and enlarges her order quantity.
TL;DR: In this paper, the authors examine standard liquidity measures to determine how well they explain the differences in the two bonds' yield spreads and find that the proxies do a poor job of measuring liquidity effects.
Abstract: Corporate bond spreads are affected by both credit risk and liquidity and it is difficult to disentangle the two factors empirically. In this paper we separate out the credit risk component by examining bonds that are issued by the same firm and that trade on the same day, allowing us to examine the effects of liquidity in a sample of bond pairs. We examine standard liquidity measures to determine how well they explain the differences in the two bonds’ yield spreads and find that the proxies do a poor job of measuring liquidity effects. Incorporating liquidity proxies related to other bonds issued by the firm and those for bonds of other firms can significantly improve the explanatory power. Still, a significant portion of the spread is left unexplained and it is largely driven by a common unknown factor. We conclude that good proxies for the liquidity component of corporate bond spreads remain elusive.
TL;DR: A comprehensive experimental comparison study over the effectiveness of four learning algorithms, i.e., BP, ELM, I-ELM, and SVM over a data set consisting of real financial data for corporate credit ratings.
TL;DR: In this paper, the authors examined the recovery rates of defaulted bonds in the US corporate bond market over the time period from 2002 to 2010, based on a complete set of traded prices and volumes.
Abstract: We examine the recovery rates of defaulted bonds in the US corporate bond market over the time period from 2002 to 2010, based on a complete set of traded prices and volumes. A detailed study of the microstructure of trading in defaulted bonds around various types of default events is provided. We document temporary price pressure with high trading volumes on the default day and the following 30 days, and low trading activity at pre-default levels thereafter. Based on these observations, market-based recovery rates in the period representing the high trading activity window are estimated. As an important additional contribution, we quantify the liquidity of defaulted bonds using various liquidity measures. We explore the relation between the recovery rates and these measures, considering additionally a comprehensive set of bond characteristics, firm fundamentals and macroeconomic variables. Our analysis explains 66% of the cross-sectional variation in recovery rates, revealing that transaction cost metrics of liquidity are particularly important variables, along with bond covenants, balance sheet ratios motivated by structural credit risk models, and macroeconomic variables. Additionally, we study the relation between price and liquidity changes in different post-default time periods.