A Note on Selecting a Response Measure for Financial Distress

Since 1966, researchers have examined financial distress prediction models to determine the usefulness of accounting information to lenders. These researchers primarily used legal bankruptcy as the response variable for economic financial distress, or included legal bankruptcy with other events in dichotomous prediction models. However, theoretical models of financial distress normally define financial distress as an economic event, the inability to pay debts when due (insolvency). This study uses a loan default/accommodation response variable as a proxy for the inability to pay debts when due. The purpose of this note is to empirically test whether or not using the inability of a firm to pay debts when due, loan default/accommodation, as a response measure produces different results than using legal bankruptcy as the response measure. The study's empirical results show that legal bankruptcy and loan default/accommodation financial distress prediction models produce different statistical results, thus suggesting that the responses measure different constructs. A loan default/accommodation model also fits the data better than a bankrupt model. Our results suggest that a loan default/accommodation response may be a more appropriate measure to determine which accounting information is most useful to lenders in evaluating a firm's credit risk.     

Pricing the Credit Risk of Secured Debt and Financial Leasing

Abstract:  This paper presents closed form solutions to price secured bank loans and financial leases subject to default risk. Secured debt fair credit spreads always increase in the debtor's default probability, whereas financial leasing fair credit spreads may well decrease in the lessee's default probability and even be negative. The reason is that the lessor, unlike the secured lender, can gain from the lessee's default, especially when the leasing contract envisages initial prepayments or the lessee's terminal options to either purchase the leased asset or to extend the lease maturity. This result, which critically depends on contractual and bankruptcy code provisions, can explain some of the empirical evidence and the use of financial leases as an alternative to secured bank lending to finance small, risky and relatively opaque firms.     

Accounting-based versus market-based cross-sectional models of CDS spreads

Models of financial distress rely primarily on accounting-based information (e.g. [Altman, E., 1968. Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. Journal of Finance 23, 589–609; Ohlson, J., 1980. Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research 19, 109–131]) or market-based information (e.g. [Merton, R.C., 1974. On the pricing of corporate debt: The risk structure of interest rates. Journal of Finance 29, 449–470]). In this paper, we provide evidence on the relative performance of these two classes of models. Using a sample of 2860 quarterly CDS spreads we find that a model of distress using accounting metrics performs comparably to market-based structural models of default. Moreover, a model using both sources of information performs better than either of the two models. Overall, our results suggest that both sources of information (accounting- and market-based) are complementary in pricing distress.     

Variable selection and corporate bankruptcy forecasts

We investigate the relative importance of various bankruptcy predictors commonly used in the existing literature by applying a variable selection technique, the least absolute shrinkage and selection operator (LASSO), to a comprehensive bankruptcy database. Over the 1980–2009 period, LASSO admits the majority of Campbell et al. (2008) predictive variables into the bankruptcy forecast model. Interestingly, by contrast with recent studies, some financial ratios constructed from only accounting data also contain significant incremental information about future default risk, and their importance relative to that of market-based variables in bankruptcy forecasts increases with prediction horizons. Moreover, LASSO-selected variables have superior out-of-sample predictive power and outperform (1) those advocated by Campbell et al. (2008) and (2) the distance to default from Merton’s (1974) structural model.     

Credit Contagion Channels: Market Microstructure Evidence from Lehman Brothers’ Bankruptcy

Immediately after Lehman Brothers’ bankruptcy, many firms disclosed their financial exposure (or lack thereof) to Lehman. This offers a clean setting to test two credit contagion channels through which a financial firm's bankruptcy can affect other firms—“counterparty risk” and “information transmission” channels. Using market microstructure variables to measure the various dimensions of contagion effects, we provide robust evidence supporting the significance of counterparty risk. Firms with exposure to Lehman suffered more severe negative effects—wider bid‐ask spread, higher price impact, greater information asymmetry, and greater selling pressure—than unexposed firms. We find mixed evidence regarding the information transmission hypothesis.     

Value investing in credit markets

We outline a parsimonious empirical model to assess the relative usefulness of accounting- and equity market-based information to explain corporate credit spreads. The primary determinant of corporate credit spreads is the physical default probability. We compare existing accounting-based and market-based models to forecast default. We then assess whether the credit market completely incorporates this default information into credit spreads. We find that credit spreads reflect information about forecasted default rates with a significant lag. This unique evidence suggests a role for value investing in credit markets.     

The effect of size on the failure probabilities of SMEs: An empirical study on the US market using discrete hazard model

This paper investigates the extent to which the size affects the SME probabilities of bankruptcy. Using a dataset of (11,117) US non-financial firms, of which (465) filed for insolvency under chapters 7/11 between 1980 and 2013. We forecast the bankruptcy probabilities by developing four discrete-time duration-dependent hazard models for SMEs, Micro, Small, and Medium firms. A comparison of the default prediction models for medium firms and SMEs suggests that an almost identical set of explanatory variables affect the default probabilities leading us to believe that treating each of these groups separately has no material impact on the decision making process. However, comparisons between the micro and small firms with the SMEs firms strongly suggest that these categories need to be considered separately when modelling their credit risk.     

德国公司违约概率预测及其对我国信用风险管理的启示

内部信用评级是新巴塞尔资本协议的核心,而违约概率的预测又是内部评级的基础。本文利用具有出色分类功能的非线性支持向量分类(SVC)方法来预测德国公司的违约概率,识别其信用风险。结果显示,SVC模型的预测能力优于基准的logit模型;而且非线性SVC模型能够捕捉线性logit模型所不能识别的影响信用风险的重要变量。本文虽然分析的是德国公司数据,但是同样对我国商业银行和公司构建全面风险管理体系有着直接的指导意义。     

Modeling default risk with support vector machines

Predicting default risk is important for firms and banks to operate successfully. There are many reasons to use nonlinear techniques for predicting bankruptcy from financial ratios. Here we propose the so-called Support Vector Machine (SVM) to predict the default risk of German firms. Our analysis is based on the Creditreform database. In all tests performed in this paper the nonlinear model classified by SVM exceeds the benchmark logit model, based on the same predictors, in terms of the performance metric, AR. The empirical evidence is in favor of the SVM for classification, especially in the linear non-separable case. The sensitivity investigation and a corresponding visualization tool reveal that the classifying ability of SVM appears to be superior over a wide range of SVM parameters. In terms of the empirical results obtained by SVM, the eight most important predictors related to bankruptcy for these German firms belong to the ratios of activity, profitability, liquidity, leverage and the percentage of incremental inventories. Some of the financial ratios selected by the SVM model are new because they have a strong nonlinear dependence on the default risk but a weak linear dependence that therefore cannot be captured by the usual linear models such as the DA and logit models.     

A note on board characteristics,ownership structure and default risk in Taiwan

This study applies dynamic generalized method of moments estimation to examine the influences of ownership structure and board characteristics on default risk for a full samples and two subsamples (high‐tech and conventional) of publicly listed firms in Taiwan. Our findings reveal that certain characteristics of corporate governance have explanatory power for default probability, but the impact is not straightforward. In particular, the impact of internal and external governance structures on default risk is industry dependent. Accordingly, governance proposals that encourage higher ownership among directors and large block shareholdings in high‐tech firms or reduce managerial ownership in conventional companies can have a counterproductive effect on corporate governance and result in higher bankruptcy possibility.     

Credit Contagion from Counterparty Risk

Standard credit risk models cannot explain the observed clustering of default, sometimes described as "credit contagion." This paper provides the first empirical analysis of credit contagion via direct counterparty effects. We find that bankruptcy announcements cause negative abnormal equity returns and increases in CDS spreads for creditors. In addition, creditors with large exposures are more likely to suffer from financial distress later. This suggests that counterparty risk is a potential additional channel of credit contagion. Indeed, the fear of counterparty defaults among financial institutions explains the sudden worsening of the credit crisis after the Lehman bankruptcy in September 2008.     

Forecasting forward defaults: a simple hazard model with competing risks

A forward default prediction method based on the discrete-time competing risk hazard model (DCRHM) is proposed. The proposed model is developed from the discrete-time hazard model (DHM) by replacing the binary response data in DHM with the multinomial response data, and thus allowing the firms exiting public markets for different causes to have different effects on forward default prediction. We show that DCRHM is a reliable and efficient model for forward default prediction through maximum likelihood analysis. We use actual panel data-sets to illustrate the proposed methodology. Using an expanding rolling window approach, our empirical results statistically confirm that DCRHM has better and more robust out-of-sample performance than DHM, in the sense of yielding more accurate predicted number of forward defaults. Thus, DCRHM is a useful alternative for studying forward default losses on portfolios.     

公司信用债违约风险预警与防范研究

我国债券规模位居世界第二,债券市场已成为企业直接融资的主要渠道;同时我国公司信用债违约频发,违约主体几乎涵盖了全部行业,永煤AAA债券违约事件引发各方关注。在此背景下,本文研究了信用债违约风险预警与防范,搭建了债券违约预警模型:一是深入分析了违约原因,提出了"经济下行加剧‘债务-通缩’""流动性分层导致再融资困难""民企互保引发违约风险串联"的观点;二是基于KLR信号分析法,以历史违约主体财报数据为基础构建了上市公司债违约预警模型,抽离出相关指标权重构成预警指标体系,并进行了实证检验;三是基于预警模型,提出加强动态监测、构建债券风险分类管理办法等政策建议。     

Employee Costs of Corporate Bankruptcy

An employee's annual earnings fall by 13% in the first full calendar year after her firm's bankruptcy, and the present value of lost earnings from bankruptcy to six years following bankruptcy is 87% of pre-bankruptcy annual earnings. More worker earnings are lost in thin labor markets and among small firms. Ex ante compensating wage differentials for this “bankruptcy risk” are up to 2% of firm value for a firm whose credit rating falls from AA to BBB, comparable in magnitude to debt tax benefits. Thus, wage premia for expected costs of bankruptcy are sufficiently large to be an important consideration in capital structure decisions.     

Optimal Capital Structure,Endogenous Bankruptcy,and the Term Structure of Credit Spreads

This article examines the optimal capital structure of a firm that can choose both the amount and maturity of its debt. Bankruptcy is determined endogenously rather than by the imposition of a positive net worth condition or by a cash flow constraint. The results extend Leland's (1994a) closed-form results to a much richer class of possible debt structures and permit study of the optimal maturity of debt as well as the optimal amount of debt. The model predicts leverage, credit spreads, default rates, and writedowns, which accord quite closely with historical averages. While short term debt does not exploit tax benefits as completely as long term debt, it is more likely to provide incentive compatibility between debt holders and equity holders. Short term debt reduces or eliminates “asset substitution” agency costs. The tax advantage of debt must be balanced against bankruptcy and agency costs in determining the optimal maturity of the capital structure. The model predicts differently shaped term structures of credit spreads for different levels of risk. These term structures are similar to those found empirically by Sarig and Warga (1989). Our results have important implications for bond portfolio management. In general, Macaulay duration dramatically overstates true duration of risky debt, which may be negative for “junk” bonds. Furthermore, the “convexity” of bond prices can become “concavity.”     

Corporate liquidity and the contingent nature of bank credit lines: Evidence on the costs and consequences of bank default

I study the impact of Lehman Brothers' bankruptcy and resultant inability to honor its obligations as a lender under committed credit lines. Firms that lost access to a credit line committed by Lehman Brothers experienced abnormal stock returns of − 3%, on average, on the day of and day after Lehman's bankruptcy filing, amounting to roughly $5.7 billion in aggregate, risk-adjusted losses. These losses were significantly larger for firms that were more financially constrained, firms with less cash, firms for whom Lehman was a lead-bank, and firms that lost access to larger amounts of committed credit. During the four quarters immediately following Lehman's collapse, firms that lost access to a credit line cut their investment spending significantly while simultaneously hoarding more cash than comparable firms. Overall, these findings indicate that firms that lost access to a credit line incurred economically significant costs and real-side consequences as a result of Lehman's default on its loan commitments.     

A simple correction of the WACC discount rate for default risk and bankruptcy costs

Standard discounted cash flow approaches suffer from a rudimental modeling of the possibility of a default, as the main characteristics such as the default probability and potential bankruptcy costs are commonly disregarded. This paper aims at providing a tractable extension of the well-known WACC approach for both default risk and bankruptcy costs. The corrected WACC discount rate reveals that default risk results in a systematically higher WACC because the tax component is scaled by the survivorship probability and an aditional component for bankruptcy costs must be added. This difference between the classical WACC discount rate and the simple modified WACC rate can be remarkable especially for firms from businesses with high bankruptcy costs and a relevant default probability.     

The Impact of Corporate Governance and Audit Quality on the Cost of Private Loans*

The objective of this paper is to examine whether banks discriminate between firms on the basis of their financial condition when assessing the credit default risk, and to what extent corporate governance and auditor quality mitigate such risks in the pricing of new bank loans. The results indicate that, depending on the probability of bankruptcy, banks rely on different monitoring devices. For firms with a low probability of bankruptcy, banks do not rely on the quality of corporate governance or the auditor's industry specialization. However, auditor tenure and a change in auditor affect the spread. For firms with a high probability of bankruptcy, the spread is adjusted for the quality of corporate governance and the auditor's specialization. These results are robust to alternative specifications and measures.     

How does credit risk affect cost management strategies? Evidence on the initiation of credit default swap and sticky cost behavior

In this paper, we examine the effect of credit defaults swaps (CDS) initiation on reference firms' cost management strategies. CDS contracts provide insurance protection for creditors, inducing a shift in bargaining power from borrowers to creditors and an excessive incidence of bankruptcy. Anticipating more intransigent creditors in debt renegotiations and higher bankruptcy risk, CDS firms are incentivized to mitigate risk through decreasing cost stickiness after CDS initiation, as cost stickiness lowers liquidity and triggers early covenant violations. We find that, on average, CDS initiation is associated with a decline in reference firms' cost stickiness. This association is more pronounced for less liquid, financially distressed, and lower credit quality firms. We also find that CDS firms with a reduction in cost stickiness will exhibit lower future bankruptcy risk than CDS firms without such as reduction in stickiness. Collectively, our findings suggest that the CDS-induced “empty creditor problem” causes reference firms to undertake more conservative cost management practices to alleviate downside risk.     

On the County-Level Credit Outcome Beta

In their pioneering work, Musto and Souleles (Journal of Monetary Economics 53(1):59–84, 2006) apply portfolio theory to consumer lending. This paper extends their work by analyzing three county-level credit outcome betas. We use the probability of default calibrated from the credit score, the actual default rate, and the actual bankruptcy rate to compute ‘score’, ‘default’, and ‘bankruptcy’ betas for each U.S. county. The correlation between default and bankruptcy betas is quite low. Counties in states in which a borrower has a right to take action against aggressive collection practices tend to have higher default betas but lower bankruptcy betas. These findings suggest the possibility of an ‘informal bankruptcy’ option for consumers. The effects of county score, default, and bankruptcy betas on the county average revolving credit line per borrower are negative. For small lenders that do not have access to the detailed historical credit files on individual consumers, the county-level beta approach of this paper might be helpful for diversifying portfolios geographically and managing risk on existing accounts.