Firm Credit Risk Research Articles

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.

Institutional investment horizon, the information environment, and firm credit risk

We provide evidence that the impact of the investment horizon of institutional investors on the credit risk of U.S. industrial firms is both statistically and economically significant. Ceteris paribus, a one percent point increase in the ownership by short-term (long-term) institutions leads to a 0.188 (.046) percentage point decrease (increase) of a firm’s credit spread during 2001–2011. However, during the financial crisis period of 2007/08, long-term institutional investors tend to reduce a firm’s credit risk, especially when a firm’s risk profile is high. Hence, long-term institutions play an important role in enhancing financial stability during the crisis period by mitigating risk.

CEO ability heterogeneity, board’s recruiting ability and credit risk

This study investigates the effects of the CEO (Chief Executive Officer) ability heterogeneity of an industry and the board’s recruiting capability on firm credit risk by using 26,235 America bond data from the year 2001 to 2014. We find that both CEO ability heterogeneity and board’s recruiting ability enhance a firm’s credit quality when controlling for other well-known determinants of bond yield spreads, implying that high CEO ability heterogeneity and good board’s recruiting ability both encourage a firm to replace the underperformed CEO earlier and improve the firm’s subsequent performance, which enhances firm value and credit quality (Merton in J Finance 29(2):449–470, 1974). We also find that good macroeconomic conditions weaken the effect of CEO ability heterogeneity on bond yield spreads while enhance that of board’s recruiting ability. Moreover, board’s recruiting ability weakens the effect of CEO ability heterogeneity on bond yield spreads, indicating that there may exist a trade-off relationship between the CEO ability heterogeneity effect and the board’s recruiting ability effect. Finally, the results are robust when considering endogeneity issues and other measures of CEO ability heterogeneity.

Credit Risk and Lottery-type Stocks: Evidence from Taiwan

This study explores the effect of credit risk on the lottery-type stocks with Taiwan's data during the sample period 2001 to 2010. The lottery-type stocks are identified as the criteria referring to Kumar [1], which have characters of lower stock price, higher idiosyncratic volatility, and higher idiosyncratic skewness. Refer to Merton [2] and Vassalou & Xing [3], a firm's credit risk is proxied by the DLI (default likelihood indicators). The main results show that the lottery-type stocks have higher default probabilities, smaller firm sizes and higher B/M (book to market) ratio comparing to the non-lottery type ones. By adding default likelihood indicator into the Carhart [4] model, the empirical results demonstrate that a firm's credit situation change has significant negative effect on return of equity; lottery-type stocks equity returns are less sensitive to default risk going higher. Furthermore, this research also shows there exists a structure change resulted from the financial tsunami, indicating the investors require more positive excess returns to compensate their risk for holding stocks after 2008 financial crisis.

Analysing the Determinants of Credit Risk for General Insurance Firms in the UK

This paper estimates a reduced-form model to assess the credit risk of General Insurance (GI) non-life firms in the UK. Compared to earlier studies, it uses a much larger sample including 30 years of data for 515 firms, and also considers a much wider set of possible determinants of credit risk. The empirical results suggest that macroeconomic and firm-specific factors both play important roles. Other key findings are the following: credit risk varies across firms depending on their business lines; there is default clustering in the GI industry; different reinsurance levels also affect the credit risk of insurance firms. The implications of these findings for regulators of GI firms under the coming Solvency II are discussed.

Nonparametric machine learning models for predicting the credit default swaps: An empirical study

Credit default swap which reflects the credit risk of a firm is one of the most frequently traded credit derivatives. In this paper, we conduct a comprehensive study to verify the predictive performance of nonparametric machine learning models and two conventional parametric models on the daily credit default swap spreads of different maturities and different rating groups, from AA to C. The whole period of data set used in this study runs from January 2001 to February 2014, which includes the global financial crisis period when the credit risk of firms were very high. Through experiments, it is shown that most nonparametric models used in this study outperformed the parametric benchmark models in terms of prediction accuracy as well as the practical hedging measures irrespective of the different credit ratings of the firms and the different maturities of their spreads. Especially, artificial neural networks showed better performance than the other parametric and nonparametric models.

Bankruptcy prediction: the case of Belgian SMEs

Purpose – The aim of this paper is to develop a bankruptcy prediction model for the Belgian small- and medium-sized enterprises (SMEs) through the building of a logit model that includes a selection of financial ratios. Design/methodology/approach – Using a sample of 7,152 Belgian SMEs among which 3,576 were declared bankrupt between 2002 and 2012, the model, which includes control variables such as firm size and age, aims to test the predictive power of ratios reflecting the financial structure, the profitability, the solvency and the liquidity of firms. Findings – The results report a satisfactory prediction accuracy and show that ratios as profitability and liquidity are excellent predictors of bankruptcy for Belgian SMEs. Research limitations/implications – Although the results seem to be conclusive, it could be noted that the healthy sample was not paired with the bankrupt sample. Other studies show that the use of paired samples makes it possible to increase the already good prediction rate. Also, further research could focus on intra-sectorial analysis. Practical implications – Beside its contribution to the academic literature on bankruptcy prediction of Belgian SMEs, this study may be of interest for investors or managers to help them to anticipate bankruptcy risks. It can also be useful for banks and other credit institutions in the assessment of credit risk of firms. Thanks to such models, they could better identify firms with a higher risk of failure in their lending decisions. Social implications – Given the increasing number of SMEs in Belgium, their significant role in the economy, the specific characteristics of the country in terms of political decision making, the institutional differences between regions and the current uncertain economic circumstances, bankruptcy prediction seems to be a necessity for the country. Originality/value – The originality of this paper lies in the fact that Belgian SMEs have been studied. This study may also be of interest to investors or managers because it may help them highlight accounting measures they should closely follow up to avoid bankruptcy.

The association between corporate general counsel and firm credit risk

This paper examines whether bond market participants alter their credit risk assessments of firms that appoint the corporate general counsel (GC) to senior management. GCs may place less emphasis on their gatekeeping responsibilities upon appointment to senior management, thus potentially resulting in increased firm credit risk. Using changes in firm-level credit ratings and credit default swap spreads to proxy for changes in credit risk, we find a positive association between GC promotions to senior management and increases in firm credit risk. Additionally, the increased personal liability for GCs under the Sarbanes–Oxley Act only partially mitigates this association.

Revaluating Firm Credit Risk The Impact of the Rating Review Process on Credit Markets

This paper analyzes the CDS spread development during the time a firm's credit rating is under review. We test whether rating agencies take on a monitoring type role with regard to firms' credit risk, thereby offering significant benefits and new information to market participants during the rating review process. We document that reviews for downgrade, which eventually result in a downgrade, lead to CDS spread increases during the time the rating is on review, whereas rating affirmations lead to a sustained reduction in spread levels. These results underline the importance of monitoring by rating agencies for credit risk valuations.

Analysing the Determinants of Credit Risk for General Insurance Firms in the UK

This paper estimates a reduced-form model to assess the credit risk of General Insurance (GI) non-life firms in the UK. Compared to earlier studies, it uses a much larger sample including 30 years of data for 515 firms, and also considers a much wider set of possible determinants of credit risk. The empirical results suggest that macroeconomic and firm-specific factors both play important roles. Other key findings are the following: credit risk varies across firms depending on their business lines; there is default clustering in the GI industry; different reinsurance levels also affect the credit risk of insurance firms. The implications of these findings for regulators of GI firms under the coming Solvency II are discussed.

Managerial Ability and Credit Risk Assessment

Research on the credit rating process has primarily focused on how rating agencies incorporate firm characteristics into their rating opinions. We contribute to this literature by examining the impact of managerial ability on the credit rating process. Given debt market participants’ interest in assessing default risk, we begin by documenting that higher managerial ability is associated with lower variability in future earnings and stock returns. We then show that higher managerial ability is associated with higher credit ratings (i.e., lower assessments of credit risk). To provide more direct identification of the impact of managerial ability, we examine chief executive officer (CEO) replacements and document that ratings increase (decrease) when CEOs are replaced with more (less) able CEOs. Finally, we show that managerial ability also has capital market implications by documenting that managerial ability is associated with bond offering credit spreads. Collectively, our evidence suggests that managerial ability is an important factor that bond market participants impound into their assessments of firm credit risk. This paper was accepted by Mary Barth, accounting.

The Effect of Ratings Announcements, on Firms in Bank-Based Systems

Rating agencies act as intermediaries for investors in evaluating the creditworthiness of borrowers. The role of ratings agencies is particularly crucial in market-based systems, because, in contrast to long-run bank relationships, outside investors are confronted with greater obstacles to in-depth and reliable evaluations of firm credit risk. The financial intermediation in bank-based systems has implications for the role and the focus of credit rating agencies. This study examines the influence of ratings announcements in Germany, one of the premier bank-based systems. During the study period, from January 2000 through June 2014, we examine 189 Standard & Poor’s and 204 Moody’s ratings announcements. Our results show that ratings announcements are less important in the German market than in market-based systems such as the United States.

The Effect of Ratings Announcements, on Firms in Bank-Based Systems

Rating agencies act as intermediaries for investors in evaluating the creditworthiness of borrowers. The role of ratings agencies is particularly crucial in market-based systems, because, in contrast to long-run bank relationships, outside investors are confronted with greater obstacles to in-depth and reliable evaluations of firm credit risk. The financial intermediation in bank-based systems has implications for the role and the focus of credit rating agencies. This study examines the influence of ratings announcements in Germany, one of the premier bank-based systems. During the study period, from January 2000 through June 2014, we examine 189 Standard & Poor’s and 204 Moody’s ratings announcements. Our results show that ratings announcements are less important in the German market than in market-based systems such as the United States.

Firm credit risk in normal times and during the crisis: are banks less risky?

Bank solvency was a major issue during the financial crisis of 2007–2009, but bank credit default swap (CDS) spreads were almost always below nonbank CDS spreads. What is the reason for this gap? Are banks perceived to be less risky? This study empirically decomposes CDS premia for 45 major banks and 167 large industrial firms from Europe and the US. It turns out that expected losses are usually somewhat lower for banks than for nonbanks, but expected losses contribute relatively little to the observed CDS premia. CDS spreads for banks and nonbanks differ mainly because market participants require a lower compensation for bearing bank credit risk. The quite persistent difference in the credit risk premia for banks and nonbanks disappears only temporarily during the crisis.

Do asset sales affect firm credit risk? – Evidence from credit rating assignments

Purpose – Asset sales can have opposing effects on firm credit quality. On the one hand asset sales could signal increased credit risk resulting from distress or on the other hand they could improve internal liquidity and hence credit quality. Therefore the impact potential asset sales can have on credit quality is an empirical question and one that has previously not been examined in the literature. The paper aims to discuss these issues. Design/methodology/approach – Using credit ratings as a measure of firm credit quality, in ordered probit regressions, this study finds evidence consistent with the internal liquidity view of the asset sales-credit risk relationship. Findings – Results from ordered probit regressions of credit ratings show that the likelihood of higher credit ratings is increasing in industry-level turnover of real assets Originality/value – Credit-rating agencies often cite the impact of asset sales on firm credit quality as a motivation for their rating assignments. Distress-driven asset sales could reduce firm credit quality whereas other asset sales could result in increased internal firm liquidity and hence improve firm credit quality. This bi-directional expectation leaves the question of how asset sales affect credit quality to be answered empirically and has not been previously tested in the literature.

Production efficiency uncertainty and corporate credit risk: Structural form credit model perspectives

Abstract This study investigates the effect of production efficiency uncertainty (PEU) on firm credit risk from structural form credit model perspectives (e.g. asset volatility) by employing 4376 American manufacturing firms' bond observations from the year 1997 to 2008. We find that PEU is positively related to firm credit risk when controlling for well-known credit risk determinant variables. We also find that booming economic conditions weaken the PEU effect. Finally, our empirical results are robust for the firm-fixed effect issue and the minimum required observations in estimating production efficiency.

The role of demographics in small business loan pricing

Demographic change influences the structure of the entrepreneurially active population, which may affect credit risk and financing conditions of small firms. Using bank internal data of small business loans in Germany, we find that the lending relationship plays a larger role for loan prices than demographics. Loan rates decrease with soft information gained through longer loan processing time and a larger number of accounts at the same bank. They increase with hard information about repayment arrears and reminders. Late payments have the largest influence on loan prices. Older entrepreneurs do not seem to be discriminated. Rather, the younger have to pay more because their loans and businesses are smaller and they lack liquidity to pay in time. Marital status and population density of the business district do not matter. This is good news for aging economies with a rising share of elderly and singles and growing disparities between peripheral and agglomerated regions.

Does the Tail Wag the Dog?: The Effect of Credit Default Swaps on Credit Risk

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.

Default probabilities of a holding company, with complete and partial information

This paper studies the valuation of credit risk for firms that own several subsidiaries or business lines. We provide simple analytical approximating expressions for probabilities of default, and for equity–debt market values, both in the case when the information is available in continuous time as well as in the case that it is not instantaneously available. The total firm’s asset value being modeled as a sum of lognormal random variables, we use convex upper and lower approximations to infer these analytical approximating expressions. We extend the model to firms financed by multiple stochastic liabilities and conclude by numerical illustrations.

Predicting Financial Stability of Select BSE Companies Revisiting Altman Z Score

In the era of globalization, prediction of financial distress is of interest not only to managers but also to external stakeholders of a company. The stakeholders are continuously seeking the optimal solution for performance forecasting, as a way to rationalize the decision-making process. The recent past shows that financial stability of companies is at the stake. Stockholders, Managers, Creditor and employees of the business are always concerned about financial stability of the companies. The most frequently tool for financial analysis is financial ratios. However, financial ratios are no-longer proved appropriate for „Stockholders‟ equity position and creditors‟ claims. Stakeholder‟s have concerns about the consequences of financial distress for companies, and controls of capital adequacy through the regulatory capital requirement (Mingo, 2000). This shared interest creates persistent investigations and continuing attempts to answer an incessant question that how financial distress can be predicted, or what reveals the credit risk of firms. For this purpose most commonly used tool is Altman Z score, but due to nature of the explanatory variables, financial distress prediction research has not reached an unequivocal conclusion. The primary goal of this paper is to analyze and reexamine the Altman Z score. In order to facilitate the current research, various ratios were taken from Altman‟s Z score. To fulfill our objective Z score ratios were used to divide sample firms into healthy and unstable among BSE-30 companies. First the Z score is calculated for 10 companies selected for this purpose for a period of 5 years each. And then it is divided as per z scores, later the significant in the changes in the ratio is calculated with the help of One sample Komogrov-Smirnow test, which resulted that the change in the z scores is not significant in case of all the companies.