Firm Credit Risk Research Articles

The Low-Carbon Transition, Climate Commitments and Firm Credit Risk

The Low-Carbon Transition, Climate Commitments and Firm Credit Risk

How Does Debt Composition Influence Credit Risk?

How do different types of debt influence firm credit risk? This paper sheds new light on this issue by decomposing the leverage ratio into market debt, bank debt, and trade credit leverage ratios by balance sheet account type classification; and short-term debt and long-term debt leverage ratios by debt maturity classification. The pecking order theory (Myers & Majluf, 1984) suggests that these debt types differ in terms of the information asymmetry. Therefore, their effects on credit risk might be distinct. We find that debt to financial markets (commercial papers, bonds, etc.) is more positively correlated with the next period's CDS spread than other debt types. CDS spread also reacts positively to bank debt leverage and responds positively to trade credit leverage only for firms in competitive sectors. With regard to maturity classification, the CDS market attributes more credit risk to long-term debt than short-term debt. We also document that the CDS market tracks firms’ accounts receivable. Our findings are also robust when we control for the credit quality of firms via credit ratings.

Corporate Social Irresponsibility and Credit Risk Prediction: A Machine Learning Approach

This paper examines the prediction accuracy of various machine learning (ML) algorithms for firm credit risk. It marks the first attempt to leverage data on corporate social irresponsibility (CSI) to better predict credit risk in an ML context. Even though the literature on default and credit risk is vast, the potential explanatory power of CSI for firm credit risk prediction remains unexplored. Previous research has shown that CSI may jeopardize firm survival and thus potentially comes into play in predicting credit risk. We find that prediction accuracy varies considerably between algorithms, with advanced machine learning algorithms (e. g. random forests) outperforming traditional ones (e. g. linear regression). Random forest regression achieves an out-of-sample prediction accuracy of 89.75% for adjusted R2 due to the ability of capturing non-linearity and complex interaction effects in the data. We further show that including information on CSI in firm credit risk prediction does not consistently increase prediction accuracy. One possible interpretation of this result is that CSI does not (yet) seem to be systematically reflected in credit ratings, despite prior literature indicating that CSI increases credit risk. Our study contributes to improving firm credit risk predictions using a machine learning design and to exploring how CSI is reflected in credit risk ratings.

The role of internal corporate governance mechanisms on default risk: A systematic review for different institutional settings

Recent financial downturns, characterized by the significant failures of firms, have revealed the need to control credit risk. Latest literature has shown that weak corporate governance structures are related to high levels of default risk, leading to financial instability. In this context, we aim to summarize the literature that focuses on the role that internal corporate governance plays in the credit risk of firms, specifically considering three corporate governance components: ownership structure, board structure and financial stakeholders’ rights and relations. Additionally, we analyse whether the effectiveness of the internal mechanisms depends on particular key factors, especially the institutional setting and the type of mechanisms considered. Finally, new lines of research are identified for future research.

Measuring credit risk in family firms

This article attempts to identify the default risk measure which best reflects the idiosyncratic context of public family firms. Seven accounting- and market-based measures are compared over a sample of 981 US family and non-family firms for the period 2000–2016. The results show that the Black–Scholes–Merton (BSM) measure gives the best fit in both types of firm. However, all the accounting-based measures, especially Altman’s Z-score, come closest to the market-based measures when used to assess the credit risk of family firms. The two types of measures also coincide more closely in their default risk orderings of family than of non-family firms. Useful practical implications can be drawn from these findings, which show that accounting-based measures can be used reliably in the absence of market data for family firms with similar characteristics to those in our sample. JEL CLASSIFICATION: G32; G33; G13; C52; M21; M41

Credit Risk and Equity Returns: An Augmented Fama-French Five-Factor Model in the Chinese Market

Whether the credit risk should be priced has been widely debated. We study this issue in the Chinese context, where the financial market has been long dominated by indirect financing. We employ the Merton’s (1974) model to measure the credit risk of firms listed on Chinese A-share market monthly. We document a positive relationship between credit risk and subsequent returns. Following a high-minus-low strategy, we construct a credit risk factor DMU, which is then incorporated into Fama-French models. By comparing the performance of 6 competing models, we find that the credit risk factor helps improve the description of portfolio returns while the investment factor makes little contribution. The conclusions are further confirmed by regression details including adjusted-R2, AIC tests and intercepts. Meanwhile, the slopes on DMU are significant for most tested portfolios and present monotonic patterns when the credit risk increases, implying that the credit risk factor can well explain the variation in the cross section of portfolio returns. Our findings show that in the Chinese context, the credit risk factor is relevant and the DMU-augmented Fama-French five-factor model is a preferred model.

Embedded value reporting quality and credit risk: evidence from life insurance companies

This study investigates the effects of releasing embedded value (EV) reports and EV report disclosure quality on life insurance companies’ credit risks, using issuer credit rating and bond yield spread data from 2001 to 2010. Results show that releasing an EV report and EV report disclosure quality are both significantly and negatively associated with life insurance companies’ credit risks. In addition, the CFO Forum (2004a, 2004b, European Embedded Value) significantly strengthens the negative effect of releasing an EV report on firm credit risk while the subprime crisis has the opposite effect in Europe. Finally, the results are robust to endogeneity issues and different model specifications of fixed effects.

Climate change and credit risk

We investigate the relationship between exposure to climate change and firm credit risk. We show that the distance-to-default, a widely used market-based measure of corporate default risk, is negatively associated with the amount of a firm’s carbon emissions and carbon intensity. Therefore, companies with high carbon footprint are perceived by the market as more likely to default, ceteris paribus. The carbon footprint decreases the distance-to-default following shocks - such as the Paris Agreement - that reveal policymakers’ intention to implement stricter climate policies. Overall, these results indicate that the exposure to climate risks affects the creditworthiness of loans and bonds issued by corporates. Financial regulators and policymakers should consider carefully the impact of climate change risks on the stability of both lending intermediaries and corporate bond markets.

Does Other Comprehensive Income Volatility Influence Credit Risk and the Cost of Debt?

ABSTRACTWe examine the usefulness of other comprehensive income (OCI) to debt investors in nonfinancial companies. Motivated by Merton's (1974) real options framework, we construct a measure of incremental OCI volatility, designed to capture the effect of OCI on overall firm asset volatility, which is a primary driver of credit risk in Merton's (1974) model. We find that the volatility of incremental OCI influences the likelihood of default, credit ratings, and the cost of debt. Overall, our evidence suggests that creditors use information from OCI in their assessment of firm credit risk and in pricing debt contracts.

CEO Bonus Pay and Firm Credit Risk

This article examines the association between the bonus component of managerial compensation and the impacts on a firm's credit risk using data from the U.S. The empirical findings suggest that bonus compensation could potentially play a role in mitigating the agency costs of debt and restraining the CEO's risk-taking behavior, as bonus pay is significantly associated with lower credit risk in a broad sample across various industries. Cash compensation including salary and bonuses, however, have different impacts on credit risk. Bonus compensation does not add to credit risk as suggested in the financial press, but firms should differentiate impacts of bonus and salary pay on firm risk when designing executives' compensation package.

Splitting Credit Risk into Systemic, Sectorial and Idiosyncratic Components

We provide a methodology to estimate a global credit risk factor from credit default swap (CDS) spreads that can be very useful for risk management. The global risk factor (GRF) reproduces quite well the different episodes that have affected the credit market over the sample period. It is highly correlated with standard credit indices, but it contains much higher explanatory power for fluctuations in CDS spreads across sectors than the credit indices themselves. The additional information content over iTraxx seems to be related to some financial interest rates. We first use the estimated GRF to analyze the extent to which the eleven sectors we consider are systemic. After that, we use it to split the credit risk of individual firms into systemic, sectorial, and idiosyncratic components, and we perform some analyses to test that the estimated idiosyncratic components are actually firm-specific. The systemic and sectorial components explain around 65% of credit risk in the European industrial and financial sectors and 50% in the North American sectors, while 35% and 50% of risk, respectively, is of an idiosyncratic nature. Thus, there is a significant margin for portfolio diversification. We also show that our decomposition allows us to identify those firms whose credit would be harder to hedge. We end up analyzing the relationship between the estimated components of risk and some synthetic risk factors, in order to learn about the different nature of the credit risk components.

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

AbstractIn 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.

Why Are Commercial Loan Rates So Sticky? The Effect of Private Information on Loan Spreads

Past studies find that commercial loan spreads are sticky in the sense that they do not fully respond to changes in open market rates or observable firm credit risk characteristics. In this paper, we provide evidence that the appearance of stickiness arises, in part, because the intensity of bank screening varies inversely with changes in both observable firm credit risk characteristics and credit market conditions. Our analysis demonstrates that stickiness in loan spreads does not necessarily indicate loan mispricing or misallocation of credit.

Half-full or half-empty? Financial institutions, CDS use, and corporate credit risk

Abstract We construct a novel dataset that matches bank holding company credit default swap (CDS) positions to detailed U.S. credit registry data containing both loan and corporate bond holdings by large U.S. banks. The dataset sheds new light on how banks use CDS, and what effects, if any, CDS use has on corporate credit risk. We show that few banks insure loans, even loans of distressed borrowers, suggesting that empty creditor problems among banks are not widespread. We find that banks are more likely to sell than buy CDS when they have a lending relationship with CDS firms. We then create new aggregate measures of hedging activity based on position-level data to test the empty creditor hypothesis. Contrary to existing studies, aggregate measures of credit risk hedging that do not condition on lending relationships overstate bank hedging activity. Furthermore, our regression results do not find any evidence that firm credit risk is adversely impacted when banks in particular purchase CDS.

Post global financial crisis modelling: credit risk for firms that are too big to fail

The global financial crisis has brought in question the validity of credit risk models. The firms that are 'too big to fail' are frequently discussed in the media, and continue to borrow rather than defaulting. In this paper we propose a new credit risk model for firms that are too big to fail. We propose a structural model of credit risk but model credit risk as a real option. We derive a closed form solution for the option to default and take into account the borrowing practices of systemically important firms. We develop our model to take into account economic factors using regime switching, and derive an option pricing solution under such a process. Finally, we obtain solutions for hedging the option to default, for markets where incompleteness exists for such options. We conduct numerical experiments to calculate the option to default at different debt values and volatility.

When do CDS spreads lead? Rating events, private entities, and firm-specific information flows

We find that credit default swap (CDS) spreads contribute significantly to price discovery in financial markets when firm-specific credit information is prominent. Using 3,470 S&P rating notch and watch changes for US public and private entities from 2001–2013, we show that CDS prices contain unique firm credit risk information that is not captured by the prices of other related securities such as stocks and bonds of the same firm. Credit information unidirectionally flows from CDS to bonds, particularly for private entities whose stocks are not concurrently trading in markets. We further find that CDS returns significantly predict stock returns, particularly their idiosyncratic components.

Risk Can Be Good: The Tradeoff Between Agency Conflicts, CEO Risk-Taking Incentives, and Credit Risk

We explore the trade-off between managerial risk-taking incentives and firm-level credit risk. Assuming that risk-taking incentives do not increase firm value, risk-taking incentives can lead to an asset substitution problem that hurts creditors. However, it is possible that risk-taking incentives will increase firm value, making creditors better off. Empirically, we find that credit rating agencies and credit default swap investors award more favorable credit ratings and credit default swap spreads, respectively, to firms that incentivize managers to engage in greater risk-taking behaviors. Consistent with recent theoretical research, we document a positive relation between managerial risk-taking incentives and firms' market value of assets. In addition, in a difference-in-differences specification, we find that increased risk-taking incentives lead to lower credit risk. Moreover, we document an incremental association between risk-taking incentives and credit risk for firms less likely to exhibit risk-shifting. Our paper is the first to empirically examine the trade-offs predicted by compensation theory from a creditor's perspective. Therefore, we extend prior literature by highlighting that creditors can benefit from risk-taking, suggesting that CEO risk-taking incentives can make both shareholders and bondholders better off. In the process, our results help reconcile conflicting views in the literature. In addition, we provide the first evidence on which firms benefit the most from risk-taking incentives: financially constrained firms. Collectively, our findings refine our understanding of why firms encourage managers to engage in risk-taking behavior.

Suppliers’/customers’ production efficiency uncertainty and firm credit risk

This study explores the effects of business counterparties’ (i.e. suppliers’/customers’) production efficiency uncertainty (PEU) on corporate credit risk by employing American bond observations of manufacturing firms. Empirical results of this study show that customers’ PEU is positively related to corporate bond yield spreads whereas suppliers’ has an opposite effect. The former result shows the importance of demand uncertainty while the latter one suggests that the benefits of supply chain integration or information sharing exceed the costs of supply chain uncertainty. We also find that the effects of suppliers’/customers’ PEUs on bond yield spreads are significantly affected by the information flow risk within the supply chain. In addition, the customer-side effect becomes weaker during the financial crisis period, whereas the supplier-side one is insignificantly affected. These empirical results are robust when controlling for potential endogeneity problems and employing an alternative sample which consists of the bond observations with both supplier and customer identification information. Finally, it has to be noticed that our conclusions are only applicable to manufacturing industries.

When Do CDS Spreads Lead? Rating Events, Private Entities, and Firm-Specific Information Flows

We find that CDS spreads contribute significantly to price discovery in financial markets when firm-specific credit information is prominent. Using 3,470 S&P rating notch and watch changes for U.S. public and private entities from 2001-2013, we show that CDS prices contain unique firm credit risk information that is not captured by the prices of other related securities such as stock and bonds of the same firm. Credit information unidirectionally flows from CDS to bonds, particularly for private entities whose stocks are not concurrently trading in markets. We further find that CDS returns significantly predict stock returns, particularly their idiosyncratic components.

Does the Variability of Other Comprehensive Income (OCI) Play a Role in the Determination of Cost of Debt, Capital Structure and Credit Ratings?

We examine the usefulness of other comprehensive income (OCI) to debt investors in nonfinancial companies. Motivated by Merton’s (1974) real options framework, we construct a measure of incremental OCI volatility, designed to capture the effect of OCI on overall firm asset volatility, which is a primary driver of credit risk in Merton’s (1974) model. We find that the volatility of incremental OCI influences the likelihood of default, credit ratings, and the cost of debt. Overall, our evidence suggests that creditors use information from OCI in their assessment of firm credit risk and in pricing debt contracts.