Modeling default probabilities: The case of Brazil

Using disaggregated data from the Brazilian stock market, we calculate default probabilities for 30 different economic sectors. Empirical results suggest that domestic macroeconomic factors can explain these default probabilities. In addition, we construct the Minimum Spanning Tree (MST) and the ultrametric hierarchical tree with the MST based on default probabilities to disclose common trends, which reveals that some sectors form clusters. The results of this paper imply that macroeconomic variables have distinct effects on default probabilities, which is important to take into account in credit risk modeling and the generation of stress test scenarios.     

Sovereign credit spreads

The paper develops a structural credit risk model to study sovereign credit risk and the dynamics of sovereign credit spreads. The model features endogenous default and recovery rates that both depend on the interaction between domestic output fluctuations and global macroeconomic conditions. We show that sovereigns choose to default at higher levels of economic output once global macroeconomic conditions are bad. This yields to default rates and credit spreads that are substantially higher compared to normal times. We derive closed-form expressions for sovereign debt values and default times and focus on the dynamics of sovereign credit spreads. As opposed to standard theories of sovereign debt, this paper’s structural model generates much richer default patterns and non-linearities through regime-shifts in the global macroeconomic environment. Moreover, changes in the global environment reveal the interconnectedness of the financial system.     

Corporate credit risk modeling and the macroeconomy

Despite a surge in the research efforts put into modeling credit and default risk during the past decade, few studies have incorporated the impact that macroeconomic conditions have on business defaults. In this paper, we estimate a duration model to explain the survival time to default for borrowers in the business loan portfolio of a major Swedish bank over the period 1994–2000. The model takes both firm-specific characteristics, such as accounting ratios and payment behaviour, loan-related information, and the prevailing macroeconomic conditions into account. The output gap, the yield curve and consumers’ expectations of future economic development have significant explanatory power for the default risk of firms. We also compare our model with a frequently used model of firm default risk that conditions only on firm-specific information. The comparison shows that while the latter model can make a reasonably accurate ranking of firms’ according to default risk, our model, by taking macro conditions into account, is also able to account for the absolute level of risk.     

A reduced form model of default spreads with Markov-switching macroeconomic factors

We examine the ability of observed macroeconomic factors and the possibility of changes in regime to explain the proportion of yield spreads caused by the risk of default in the context of a reduced form model. For this purpose, we extend the Markov-switching risk-free term structure model of Bansal and Zhou (2002) to the corporate bond setting and develop recursive formulas for default probabilities, risk-free and risky zero-coupon bond yields as well as credit default swap premia. The model is calibrated with consumption, inflation, risk-free yields and default data for Aa, A and Baa bonds from the 1987 to 2008 period. We find that our macroeconomic factors are linked with two out of three sharp increases in the spreads during this sample period, indicating that the spread variations can be related to macroeconomic undiversifiable risk.     

Market conditions,default risk and credit spreads

This study empirically examines the impact of the interaction between market and default risk on corporate credit spreads. Using credit default swap (CDS) spreads, we find that average credit spreads decrease in GDP growth rate, but increase in GDP growth volatility and jump risk in the equity market. At the market level, investor sentiment is the most important determinant of credit spreads. At the firm level, credit spreads generally rise with cash flow volatility and beta, with the effect of cash flow beta varying with market conditions. We identify implied volatility as the most significant determinant of default risk among firm-level characteristics. Overall, a major portion of individual credit spreads is accounted for by firm-level determinants of default risk, while macroeconomic variables are directly responsible for a lesser portion.     

Default and Recovery Risk Dependencies in a Simple Credit Risk Model

This paper provides evidence for the relationship between credit quality, recovery rate, and correlation. The paper finds that rating grade, rating shift, and macroeconomic factors provide a highly significant explanation for default risk and recovery risk of US bond issues. The empirical data suggest that default and recovery processes are highly correlated. Therefore, a joint approach is required for estimating time‐varying default probabilities and recovery rates that are conditional on default. This paper develops and applies such a model.     

Renegotiation of financial contracts: Evidence from private credit agreements

Using a large sample of private credit agreements between U.S. publicly traded firms and financial institutions, we show that over 90% of long-term debt contracts are renegotiated prior to their stated maturity. Renegotiations result in large changes to the amount, maturity, and pricing of the contract, occur relatively early in the life of the contract, and are rarely a consequence of distress or default. The accrual of new information concerning the credit quality, investment opportunities, and collateral of the borrower, as well as macroeconomic fluctuations in credit and equity market conditions, are the primary determinants of renegotiation and its outcomes. The terms of the initial contract (e.g., contingencies) also play an important role in renegotiations; by altering the structure of the contract in a state contingent manner, renegotiation is partially controlled by the contractual assignment of bargaining power.     

Default Risk Estimation,Bank Credit Risk,and Corporate Governance

This study explores the relationship between credit risks of banks and the corporate governance structures of these banks from the perspective of creditors. The cumulative default probabilities are estimated for a sample of US commercial and savings banks to measure their risk taking behavior. The results show that one year and five year cumulative default probabilities are time‐varying, with a significant jump observed in the year prior to the financial crisis of 2008–09. Generally speaking, corporate governance structures have a greater impact on US commercial banks than on savings institutions. We provide evidence that, after controlling for firm specific characteristics, commercial banks with larger boards and older CFOs are associated with significantly lower credit risk levels. Lower ownership by institutional investors and more independent boards also have lower credit risk levels, although these effects are somewhat less significant. For all the banks in our sample, large board size, older CFO, and less busy directors are associated with lower credit risk levels. When we restrict the sample to consider the joint effects of the governance variables, the results on board size and busy directors are maintained.     

An analysis of default correlations and multiple defaults

Evaluating default correlations or the probabilities of defaultby more than one firm is an important task in credit analysis,derivatives pricing, and risk management. However, default correlationscannot be measured directly, multiple-default modeling is technicallydifficult, and most existing credit models cannot be appliedto analyze multiple defaults. This article develops a first-passage-timemodel, providing an analytical formula for calculating defaultcorrelations that is easily implemented and conveniently usedfor a variety of financial applications. The model also providesa theoretical justification for several empirical regularitiesin the credit risk literature.     

Credit spread interdependencies of European states and banks during the financial crisis

We investigate the interdependence of the default risk of several Eurozone countries (France, Germany, Italy, Ireland, the Netherlands, Portugal, and Spain) and their domestic banks during the period between June 2007 and May 2010, using daily credit default swaps (CDS). Bank bailout programs changed the composition of both banks’ and sovereign balance sheets and, moreover, affected the linkage between the default risk of governments and their local banks. Our main findings suggest that in the period before bank bailouts the contagion disperses from bank credit spreads into the sovereign CDS market. After bailouts, a financial sector shock affects sovereign CDS spreads more strongly in the short run. However, the impact becomes insignificant in the long term. Furthermore, government CDS spreads become an important determinant of banks’ CDS series. The interdependence of government and bank credit risk is heterogeneous across countries, but homogeneous within the same country.     

Correlation in credit risk changes

The current economic climate makes understanding credit risk correlation particularly important. After allowing for a comprehensive set of observable firm-specific, industry, market, and macroeconomic factors, there is an economically significant co-movement in credit default swap spreads that remains to be explained. Including a time dummy completely accounts for the remaining co-movement, confirming the existence of a systematic component that has been previously unaccounted for. Our findings suggest that it may be important to consider unobservable risk factor(s) in credit risk models.     

A framework for assessing the systemic risk of major financial institutions

In this paper we propose a framework for measuring and stress testing the systemic risk of a group of major financial institutions. The systemic risk is measured by the price of insurance against financial distress, which is based on ex ante measures of default probabilities of individual banks and forecasted asset return correlations. Importantly, using realized correlations estimated from high-frequency equity return data can significantly improve the accuracy of forecasted correlations. Our stress testing methodology, using an integrated micro–macro model, takes into account dynamic linkages between the health of major US banks and macro-financial conditions. Our results suggest that the theoretical insurance premium that would be charged to protect against losses that equal or exceed 15% of total liabilities of 12 major US financial firms stood at $110 billion in March 2008 and had a projected upper bound of $250 billion in July 2008.     

A comparative study of the probability of default for global financial firms

This article presents a modification of Merton’s (1976) ruin option pricing model to estimate the implied probability of default from stock and option market prices. To test the model, we analyze all global financial firms with traded options in the US and focus on the subprime mortgage crisis period. We compare the performance of the implied probability of default from our model to the expected default frequencies based on the Moody’s KMV model and agency credit ratings by constructing cumulative accuracy profiles (CAP) and the receiver operating characteristic (ROC). We find that the probability of default estimates from our model are equal or superior to other credit risk measures studied based on CAP and ROC. In particular, during the subprime crisis our model surpassed credit ratings and matched or exceeded KMV in anticipating the magnitude of the crisis. We have also found some initial evidence that adding off-balance-sheet derivatives exposure improves the performance of the KMV model.     

Systematic stress tests with entropic plausibility constraints

Stress tests with handpicked scenarios might misrepresent risks either because dangerous scenarios are not considered or because the scenarios considered are too implausible. To overcome these two pitfalls we propose a systematic search for the worst case within a relative entropy ball of sufficiently plausible scenarios. For this purpose we use mixed scenarios, which are risk factor distributions rather than realisations. A Maximum Loss theorem explicitly gives the worst case distribution. The method is illustrated in a number of example applications: linear and quadratic portfolios, stressed default probabilities, stressed correlations, macroeconomic stress tests.     

Macroeconomic Conditions and the Puzzles of Credit Spreads and Capital Structure

I build a dynamic capital structure model that demonstrates how business cycle variation in expected growth rates, economic uncertainty, and risk premia influences firms' financing policies. Countercyclical fluctuations in risk prices, default probabilities, and default losses arise endogenously through firms' responses to macroeconomic conditions. These comovements generate large credit risk premia for investment grade firms, which helps address the credit spread puzzle and the under‐leverage puzzle in a unified framework. The model generates interesting dynamics for financing and defaults, including market timing in debt issuance and credit contagion. It also provides a novel procedure to estimate state‐dependent default losses.     

Asymmetric effects of the business cycle on bank credit risk

Prior empirical research on the relation between credit risk and the business cycle has failed to properly investigate the presence of asymmetric effects. To fill this gap, we examine this relation both at the aggregate and the bank level exploiting a unique dataset on Italian banks’ borrowers’ default rates. We employ threshold regression models that allow to endogenously establish different regimes identified by the thresholds over/below which credit risk is more/less cyclical. We find that not only are the effects of the business cycle on credit risk more pronounced during downturns but cyclicality is also higher for those banks with riskier portfolios.     

Capital structure,credit risk,and macroeconomic conditions

This paper develops a framework for analyzing the impact of macroeconomic conditions on credit risk and dynamic capital structure choice. We begin by observing that when cash flows depend on current economic conditions, there will be a benefit for firms to adapt their default and financing policies to the position of the economy in the business cycle phase. We then demonstrate that this simple observation has a wide range of empirical implications for corporations. Notably, we show that our model can replicate observed debt levels and the countercyclicality of leverage ratios. We also demonstrate that it can reproduce the observed term structure of credit spreads and generate strictly positive credit spreads for debt contracts with very short maturities. Finally, we characterize the impact of macroeconomic conditions on the pace and size of capital structure changes, and debt capacity.     

THE INFORMATIONAL ROLE OF BANK LOAN RATINGS

We analyze the relatively new phenomenon of credit ratings on syndicated loans, asking first whether they convey information to the capital markets. Our event studies show that initial loan ratings and upgrades are not informative, but downgrades are. The market anticipates downgrades to some extent, however. We also examine whether public information reflecting borrower default characteristics explains cross‐sectional variation in loan ratings and find that ratings are only partially predictable. Our evidence suggests that loan and bond ratings are not determined by the same model. Finally, we estimate a credit spread model incorporating bank loan ratings and other factors reflecting default risk, information asymmetry, and agency problems. We find that ratings are related to loan rates, given the effect of other influences on yields, suggesting that ratings provide information not reflected in financial information. Ratings may capture idiosyncratic information about recovery rates, as each of the agencies claims, or information about default prospects not available to the market.     

Theory and evidence on the dynamic interactions between sovereign credit default swaps and currency options

Using sovereign CDS spreads and currency option data for Mexico and Brazil, we document that CDS spreads covary with both the currency option implied volatility and the slope of the implied volatility curve in moneyness. We propose a joint valuation framework, in which currency return variance and sovereign default intensity follow a bivariate diffusion with contemporaneous correlation. Estimation shows that default intensity is much more persistent than currency return variance. The market price estimates on the two risk factors also explain the well-documented evidence that historical average default probabilities are lower than those implied from credit spreads.     

Credit cycles and macro fundamentals

We use an intensity-based framework to study the relation between macroeconomic fundamentals and cycles in defaults and rating activity. Using Standard and Poor's U.S. corporate rating transition and default data over the period 1980–2005, we directly estimate the default and rating cycle from micro data. We relate this cycle to the business cycle, bank lending conditions, and financial market variables. In line with earlier studies, the macro variables appear to explain part of the default cycle. However, we strongly reject the correct dynamic specification of these models. The problem is solved by adding an unobserved dynamic component to the model, which can be interpreted as an omitted systematic credit risk factor. By accounting for this latent factor, many of the observed macro variables loose their significance. There are a few exceptions, but the economic impact of the observed macro variables for credit risk remains low. We also show that systematic credit risk factors differ over transition types, with risk factors for downgrades being noticeably different from those for upgrades. We conclude that portfolio credit risk models based only on observable systematic risk factors omit one of the strongest determinants of credit risk at the portfolio level. This has obvious consequences for current modeling and risk management practices.