Credit risk drivers: Evaluating the contribution of firm level information and of macroeconomic dynamics

Understanding if credit risk is driven mostly by idiosyncratic firm characteristics or by systematic factors is an important issue for the assessment of financial stability. By exploring the links between credit risk and macroeconomic developments, we observe that in periods of economic growth there may be some tendency towards excessive risk-taking. Using an extensive dataset with detailed information for more than 30 000 firms, we show that default probabilities are influenced by several firm-specific characteristics. When time-effect controls or macroeconomic variables are also taken into account, the results improve substantially. Hence, though the firms’ financial situation has a central role in explaining default probabilities, macroeconomic conditions are also very important when assessing default probabilities over time.     

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.     

Multi-period corporate default prediction with stochastic covariates

We provide maximum likelihood estimators of term structures of conditional probabilities of corporate default, incorporating the dynamics of firm-specific and macroeconomic covariates. For US Industrial firms, based on over 390,000 firm-months of data spanning 1980 to 2004, the term structure of conditional future default probabilities depends on a firm's distance to default (a volatility-adjusted measure of leverage), on the firm's trailing stock return, on trailing S&P 500 returns, and on US interest rates. The out-of-sample predictive performance of the model is an improvement over that of other available models.     

Macroeconomic effects of corporate default crisis: A long-term perspective

Using an extensive data set on corporate bond defaults in the US from 1866 to 2010, we study the macroeconomic effects of bond market crises and contrast them with those resulting from banking crises. During the past 150 years, the US has experienced many severe corporate default crises in which 20–50% of all corporate bonds defaulted. Although the total par amount of corporate bonds has at times rivaled the amount of bank loans outstanding, we find that corporate default crises have far fewer real effects than do banking crises. These results provide empirical support for current theories that emphasize the unique role that banks and the credit and collateral channels play in amplifying macroeconomic shocks.     

Incorporating the dynamics of leverage into default prediction

A firm’s current leverage ratio is one of the core characteristics of credit quality used in statistical default prediction models. Based on the capital structure literature, which shows that leverage is mean-reverting to a target leverage, we forecast future leverage ratios and include them in the set of default risk drivers. An out-of-sample analysis of default predictions from a hazard model reveals that the discriminative power increases substantially when leverage forecasts are included. We further document that credit ratings contain information beyond the one contained in standard variables but that this information is unrelated to forecasts of leverage ratios.     

Macroeconomic risk and the cross-section of stock returns

We develop a conditional version of the consumption capital asset pricing model (CCAPM) using the conditioning variable from the cointegrating relation among macroeconomic variables (dividend yield, term spread, default spread, and short-term interest rate). Our conditioning variable has a strong power to predict market excess returns in the presence of competing predictive variables. In addition, our conditional CCAPM performs approximately as well as Fama and French’s (1993) three-factor model in explaining the cross-section of the Fama and French 25 size and book-to-market sorted portfolios. Our specification shows that value stocks are riskier than growth stocks in bad times, supporting the risk-based story.     

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.     

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 control, political costs and earnings management: Evidence from Chinese listed real estate companies

Firms in China have faced high political costs during China’s economic transition, because they are affected by macroeconomic policies. However, research to date has offered no consistent conclusions on the relationship between political costs and earnings management in China. This study tests whether real estate firms attempt to decrease earnings during periods of macroeconomic control, using variables related to the national real estate market as proxies for political costs. We find that political costs are negatively related to earnings management in listed real estate firms. In addition, we find that non-state-owned enterprises utilized more income-decreasing accruals during this period. Our results are consistent with the political costs hypothesis.     

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.     

Legislative demands and economic realities: Company and group accounts compared

In many countries, not only one but several sets of accounts have to be prepared and disclosed by (holding) companies. This paper investigates the possibly different economic functions of these sets of accounts by looking at the German dual financial reporting system, in which company (single) and group (consolidated) accounts have to be published. Using a large number of accounting- and market-based metrics, we test whether single and group accounts display different properties and—if so—whether this finding can be explained by different economic roles played by both sets of accounts. Indeed, properties are found to differ. However, there is no evidence for single accounts being equally or more useful than group accounts in valuation and contracting. There is also no evidence that single accounts play a superior role in determining future dividend payouts or predicting default probabilities. Moreover, single accounts do not play an incremental role in fulfilling these functions either. Our results indicate that the factual role of single accounts is to provide the basis to compute taxable income. We do not consider this an economic function in its own right but, rather, as a legal requirement that can possibly be achieved by less costly means.     

The effect of macroeconomic news on stock returns: New evidence from newspaper coverage

Previous literature has produced weak evidence to support the hypothesis that real economic news affects stock returns. This is, in part, attributed to the difficulty of measuring how investors interpret macroeconomic announcements in different economic environments. In this paper, we choose a different approach of measuring macroeconomic news to better estimate its effect on stock returns. Since newspaper stories provide an interpretation of the statistical releases, we choose newspaper stories as our measure of news. Our findings indicate that news about GDP and unemployment does affect stock returns.     

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.     

Assessing Corporate Vulnerabilities in Indonesia: A Bottom-Up Default Analysis

Under adverse macroeconomic conditions, the potential realization of corporate sector vulnerabilities could pose major risks to the economy. This paper assesses corporate vulnerabilities in Indonesia by using a Bottom-Up Default Analysis (BuDA) approach, which allows projecting corporate probabilities of default (PDs) under different macroeconomic scenarios. In particular, a protracted recession and the ensuing currency depreciation could erode buffers on corporate balance sheets, pushing up the probabilities of default (PDs) in the corporate sector to the high levels observed during the Global Financial Crisis. While this is a low-probability scenario, the results suggest the need to closely monitor vulnerabilities and strengthen contingency plans.     

New evidence on oil price and firm returns

In this paper, we examine the relationship between oil price and firm returns for 560 US firms listed on the NYSE. First, we find that oil price affects returns of firms differently depending on their sectoral location. Second, we find strong evidence of lagged effect of oil price on firm returns. Third, we test whether oil price affects firm returns based on different regimes and find that in five out of the 14 sectors this is indeed the case. Finally, we unravel that oil price affects firm returns differently based on firm size, implying strong evidence of size effects.     

Death and jackpot: Why do individual investors hold overpriced stocks?

Campbell, Hilscher, and Szilagyi (2008) show that firms with a high probability of default have abnormally low average future returns. We show that firms with a high potential for default (death) also tend to have a relatively high probability of extremely large (jackpot) payoffs. Consistent with an investor preference for skewed, lottery-like payoffs, stocks with high predicted probabilities for jackpot returns earn abnormally low average returns. Stocks with high death or jackpot probabilities have relatively low institutional ownership and the jackpot effect we find is much stronger in stocks with high limits to arbitrage.     

Modelling the distribution of credit losses with observable and latent factors

This paper proposes a dynamic model to estimate the credit loss distribution of the aggregate portfolio of loans granted in a banking system. We consider a sectoral approach distinguishing between corporates and households. The evolution of their default frequencies and the size of the loans portfolio are expressed as functions of macroeconomic conditions as well as unobservable credit risk factors, which capture contagion effects between sectors. In addition, we model the distributions of the Exposures at Default and the Losses Given Default. We apply our framework to the Spanish banking system, where we find that sectoral default frequencies are not only affected by economic cycles but also by a persistent latent factor. Finally, we identify the riskier sectors, perform stress tests and compare the relative risk of small and large institutions.     

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.     

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.     

Checking for asymmetric default dependence in a credit card portfolio: A copula approach

Traditional credit risk models adopt the linear correlation as a measure of dependence and assume that credit losses are normally-distributed. However some studies have shown that credit losses are seldom normal and the linear correlation does not give accurate assessment for asymmetric data. Therefore it is possible that many credit models tend to misestimate the probability of joint extreme defaults.This paper employs Copula Theory to model the dependence across default rates in a credit card portfolio of a large UK bank and to estimate the likelihood of joint high default rates. Ten copula families are used as candidates to represent the dependence structure. The empirical analysis shows that, when compared to traditional models, estimations based on asymmetric copulas usually yield results closer to the ratio of simultaneous extreme losses observed in the credit card portfolio.Copulas have been applied to evaluate the dependence among corporate debts but this research is the first paper to give evidence of the outperformance of copula estimations in portfolios of consumer loans. Moreover we test some families of copulas that are not typically considered in credit risk studies and find out that three of them are suitable for representing dependence across credit card defaults.