Do private equity owners increase risk of financial distress and bankruptcy?

In this study, we investigate financial distress risks of European companies around the buyout event in the period between 2000 and 2008. In addition, we analyze whether buyout companies go bankrupt more often than comparable non-buyout companies. Our results suggest that private equity investors select companies which are less financially distressed than comparable non-buyout companies and that the distress risk increases after the buyout. Despite this increase, private equity-backed companies do not suffer from higher bankruptcy rates than comparable non-buyout companies. In fact, when companies are backed by experienced private equity funds, their bankruptcy rates are even lower. These findings indicate that experienced investors are better able to manage distress risks than their inexperienced counterparts.     

上市公司财务状况分类研究

如何对众多上市公司的财务状况进行合理分类 ,判别公司的财务处境 ,进而指导公司的财务行为 ,对于公司财务政策的制定具有重要意义。本文突破以往文献将企业财务状况仅仅基于“好”与“坏”标准进行简单分类、即财务困境企业和非财务困境企业的界限 ,在理论上首次将公司的财务状况分为五类 ,即财务闲置、财务充盈、财务均衡、财务困境和财务破产。实证研究表明 ,我国上市公司确存在五种财务状况 ,支持理论假设 ,进一步 ,我们发现 ,中国上市公司普遍存在财务状况不佳的现象 ,隐性财务破产的上市公司多于证券市场上实际披露的数目。     

Economic Distress, Financial Distress, and Dynamic Liquidation

Many firms emerging from a debt restructuring remain highly leveraged, continue to invest little, perform poorly, and often reenter financial distress. The existing literature interprets these findings as inefficiencies arising from coordination problems among many creditors or an inefficient design of bankruptcy law. In contrast, this paper emphasizes that creditors lack the information that is needed to make quick and correct liquidation decisions. It can explain the long-term nature of financial distress solely as the result of dynamic learning strategies of creditors and suggests that it may be an unavoidable byproduct of an efficient resolution of financial distress.     

Model Predictions and Auditor Assessments of Going Concern Status

This paper compares the predictions of a bankruptcy prediction model and the assessments of auditors on the going concern status of a sample of 165 bankrupt companies and 165 matched non-bankrupt companies. Data from US companies for the period 1978 to 1985 were used. Probit analysis (with the weighted exogenous sampling maximum likelihood procedure) was applied to estimate the model parameters. The Lachenbruch U method hold-out accuracy rates of the model are 85.45% for bankrupt firms, 100.00% for non-bankrupt firms, and 99.91% overall. The corresponding accuracy rates of the auditors based on their audit reports are 54.37% for bankrupt firms, 100.00% for non-bankrupt firms, and 99.73% overall. The sensitivity of optimal cut-off points to misclassification costs of Type I and Type II errors was also considered. Results of the study suggest that bankruptcy prediction models can be useful to auditors in making going concern assessments. Further, such models can serve as analytical tools and defensive devices.     

Can Language Predict Bankruptcy? The Explanatory Power of Tone in 10‐K Filings

We examine whether the language used in 10‐K filings reflects a firm's risk of bankruptcy. Our sample contains 424 bankrupt U.S. companies in the period 1994–2015 and we use propensity score matching to find healthy matches. Based on a logit model of failing and vital firms, our findings indicate that firms at risk of bankruptcy use significantly more negative words in their 10‐K filings than comparable vital companies. This relationship holds up until three years prior to the actual bankruptcy filing. With our investigation, we confirm the results from previous accounting and finance research. 10‐K filings contain valuable information beyond the reported financials. Additionally, we show that 10‐Ks filed in the year of a firm's collapse contain an increased number of litigious words relative to healthy businesses. This indicates that the management of failing firms is already dealing with legal issues when reporting financials prior to bankruptcy. Our results suggest that analysts ought to include the presentation of financials in their assessment of bankruptcy risk as it contains explanatory and predictive power beyond the financial ratios.     

Predicting Bankruptcy Resolution

This study examines classification and prediction of the bankruptcy resolution event. Filing of bankruptcy is resolved through one of three alternative resolutions: acquisition, emergence or liquidation. Predicting the final bankruptcy resolution has not been examined in the prior accounting and finance literature. This post-bankruptcy classification and prediction of the final resolution is harder than discriminating between healthy and bankrupt firms because all filing firms are already in financial distress. Motivation for predicting the final resolution is developed and enhanced. A sample of 237 firms filing for bankruptcy is used. Classification and prediction accuracies are determined using a logit model. A ten-variable, three-group resolution logit model, which includes five accounting and five non-accounting variables is developed. The model correctly classifies 62 percent of the firms, significantly better than a random classification. We conclude that non-accounting data add relevant information to financial accounting data for predicting post bankruptcy resolution. Further, public policy implications for investors, researchers, bankruptcy judges, claimants and other stakeholders are discussed.     

Cash-flow shortage as an endogenous bankruptcy reason

This paper develops a simple model for a leveraged firm and endogenizes the firm’s bankruptcy point by assuming that equity issuance is costly. Equity-issuance costs reflect the difficulties in issuing new equity for firms that are close to financial distress. The resulting model captures cash-flow shortage as a reason to go bankrupt, though the equity value is positive. I analyze the optimal bankruptcy point as well as corporate bond prices and yield spreads for various levels of equity-issuance costs in order to study the impact of different liquidity constraints. Finally, I discuss the consequences on optimal capital structure.     

系统性风险与企业财务危机预警——基于前沿机器学习的新视角

本文采用Logit回归模型以及随机森林模型、梯度提升模型等前沿机器学习方法,深入考察系统性风险指标对我国企业财务危机的预测能力。结果表明,系统性风险对中下游企业的财务危机具有显著的预测能力,而基于因子分析构建的系统性风险指标,结合随机森林模型可取得更好的预测效果。本文进一步区分财务危机的不同成因并发现,基于随机森林模型和Logit回归模型的预测框架能够对我国大多数财务危机事件进行有效预警。在此基础上,本文对我国上市企业监管提出相关建议,从而为完善金融风险处置机制提供一定参考。     

Does pre‐packed bankruptcy create value? An empirical study of postbankruptcy employment retention in The Netherlands

In recent years, there has been growing interest in whether pre‐packed bankruptcy can be a mechanism through which firms facing imminent insolvency can preserve value. Although an extensive body of literature exists on “pre‐packs,” whether such techniques really preserve value remains ambiguous. By analysing bankruptcy proceedings filed with Dutch courts in the period 2012–2018 through the lenses of real options and debt overhang theory, we examined employment retention postbankruptcy as a consequence of the type of bankruptcy proceeding (pre‐packed bankruptcy and conventional bankruptcy) and the severity of prebankruptcy financial distress. The results show that in the Netherlands, a pre‐packed bankruptcy, when compared with a conventional bankruptcy proceeding, positively impacts employment retention rates after bankruptcy. The severity of financial distress before bankruptcy does not affect employment retention rates postbankruptcy. This implies that despite the amount of resource slack, the preservation of employee value is better served under a pre‐packed bankruptcy than a conventional bankruptcy proceeding. This finding is important for insolvency practice, as up to 22 June 2017, employee rights in the Netherlands (including redundancy) were not considered to be automatically transferred to the firm acquiring the bankrupt debtor's assets when a pre‐packed bankruptcy was applied. Implications for insolvency regulation and practice are discussed.     

The endogenous relationship between audit-report type and business termination: evidence on private firms in a non-litigious environment

This study provides evidence on the relationship between audit-report type and subsequent business termination for private companies in a non-litigious environment. The results show that an endogenous relationship exists between bankruptcy and audit-report type, and between voluntary liquidation and audit-report type. A non-clean opinion is typically issued when firms face financial difficulties, which in turn become more severe after the receipt of a non-clean audit opinion. We find evidence that, even without a litigation deterrent in Belgium, financial performance has a similar impact on audit-report type as in litigious environments. We find that the self-fulfilling prophecy hypothesis holds for bankruptcy but not for voluntary liquidation. Our study also provides some evidence on audit reporting differences between Big 6 and non-Big 6 auditors in the Belgian audit market. When financial difficulties are obvious, as is the case when a company is about to go bankrupt, both Big 6 and non- Big 6 auditors are as competent and/or independent to assess and report going-concern problems. However, when financial difficulties are less apparent, as is the case for firms that voluntarily decide to liquidate, our results indicate that Big 6 auditors are more likely to issue a non-clean audit opinion than non-Big 6 auditors.     

Investing in Bankrupt Firms

We examine the investment characteristics of firms electing to enter bankruptcy, between 1973 and 1982. Comparisons are made before and after the Bankruptcy Reform Act of 1978. Our results indicate that the 1978 Act had no significant impact on bankruptcy decisions or resolutions for actively traded firms. Trading in bankrupt firms' securities is becoming more common, but no abnormal returns appear to be available. Systematic risk does not change significantly with the filing of bankruptcy, but there is a significant increase in return variance. The financial markets also react to various announcements of stages in the reorganization process.     

Evidence from impending bankrupt firms that long horizon institutional investors are informed about future firm value

A key assumption in many accounting and finance studies is that long horizon institutional investors are informed shareholders. Yet past empirical research finds no evidence that these institutions anticipate major corporate events, including earnings-based events. I find that long horizon institutions are better informed in that they sell more shares of impending bankrupt firms than of matched distress firms at least one quarter ahead of bankruptcy. Share sales are greater in impending bankrupt firms whose shareholders ultimately lose all of their equity. In additional analyses, I document greater share sales by long horizon institutions with supposedly superior information processing abilities and/or access to corporate management. Share sales are significantly less in the post Regulation FD era. Overall, my findings support the validity of the common assumption that long horizon institutions are informed. Regulation FD appears to mitigate (but not eliminate) their information advantage.     

Beyond bankruptcy: Does the US bankruptcy code provide a fresh start to entrepreneurs?

This paper assesses the extent to which the US bankruptcy system is effective in providing small businesses a “fresh start” after a bankruptcy filing. I use data from the 1993, 1998 and 2003 National Survey of Small Business Finances to explore how firms fare after a bankruptcy filing. On the positive side, previously bankrupt firms are not any more burdened than the average small firm by problems relating to profitability, cash flow, health insurance costs, or taxes. Further, the fact that these firms are surviving several years after the filing is itself a testament to the efficient functioning of the US bankruptcy system. It suggests that the bankruptcy system goes a long way toward helping businesses recover after a bankruptcy filing.     

The financial distress pricing puzzle in banking firms

This paper examines whether the financial distress pricing puzzle observed for non-financial firms is also observed for financial firms and how this puzzle differs according to the extent of short-sale constraints. By using the eight distress measures developed for financial firms, we find that there is a strong negative relation in the cross-section between financial distress and subsequent bank stock returns, regardless of adjustment for risk. However, this distress pricing puzzle is statistically significant only for high short-sale constrained banks, but not for low short-sale constrained banks. Thus, short-sale constraints are at least one non-risk attribute that causes the distress pricing puzzle for financial firms. We also find that despite its simple form, compared to the other complex distress measures, non-performing loans (NPLs) are the most informative in predicting future bank stock returns as well as bankruptcy and failure.     

Using a hybrid evolution approach to forecast financial failures for Taiwan-listed companies

Bankruptcy has been an important topic in finance and accounting research for a long time. Recent major bankruptcies have included seemingly robust companies such as Enron, Kmart, Global Crossing, WorldCom, and Lehman Brothers. These cases have become of serious public concern due to the huge influence these companies have on the real economy. This research proposes a hybrid evolution approach to integrate particle swarm optimization (PSO) with the support vector machine (SVM) technique for the purpose of predicting financial failures. The preparation phase collected an initial sample of 68 companies listed by the Taiwan Stock Exchange Corporation (TSEC). The financial datasets were constructed based on 33 financial ratios, four non-financial ratios and one combined macroeconomic index. To select suitable indicators for the input vector, the principle component analysis (PCA) technique was applied to reduce the data and determine how groupings of indicators measure the same concept. In the swarming phase, PSO was applied to obtain suitable parameters for SVM modeling without reducing the classification accuracy rate. In the modeling phase, the SVM model was used to build a training set that was used to calculate the model's accuracy and fitness value. Finally, these optimized parameters were used in the hybrid PSO–SVM model to evaluate the model's predictive accuracy. This paper provides four critical contributions. (1) Using the PCA technique, the statistical results indicate that the financial prediction performance is mainly affected by financial ratios rather than non-financial and macroeconomic ratios. (2) Even with the input of nearly 70% fewer indicators, our approach is still able to provide highly accurate forecasts of financial bankruptcy. (3) The empirical results show that the PSO–SVM model provides better classification accuracy (i.e. normal vs. bankrupt) than the grid search (Grid–SVM) approach. (4) For six well-known UCI datasets, the PSO–SVM model also provides better prediction accuracy than the Grid–SVM, GA–SVM, SVM, SOM, and SVR–SOM approaches. Therefore, this paper proposes that the PSO–SVM approach is better suited for predicting potential financial distress.     

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.     

Why and How UK Firms Hedge

This paper attempts to differentiate among the theories of hedging by using disclosures in the annual reports of 400 UK companies and data collected via a survey. I find, unlike many previous US studies, strong evidence linking the decision to hedge and the expected costs of financial distress. The tests show that this is mainly because my definition of hedging includes all hedgers and not just derivative users. However, when the tests employ the same hedging definition as previous US studies, financial distress cost factors still appear to be more important for this sample than samples of US firms. Therefore, a secondary explanation for the strong financial distress results might be due to differences in the bankruptcy codes in the two countries, which result in higher expected costs of financial distress for UK firms. The paper also examines the determinants of the choice of hedging method distinguishing between non‐derivative and derivatives hedging. My evidence shows that larger firms, firms with more cash, firms with a greater probability of financial distress, firms with exports or imports and firms with more short‐term debt are more likely to hedge with derivatives. Thus, differences in opportunities, in incentives for reducing risk and in the types of financial price exposure play an important role in how firms hedge their risks.     

The Interaction of Solvency with Liquidity and its Association with Bankruptcy Emergence

Prior research has shown that accounting information available prior to a bankruptcy is associated with the likelihood of bankruptcy. We show that additionally, the accounting information available prior to bankruptcy is associated with whether or not a firm will emerge from bankruptcy. We predict that firms that exhibit low solvency risk and high liquidity risk are most likely to emerge from bankruptcy. Firms that exhibit high solvency risk and high liquidity risk are predicted to be least likely to emerge from bankruptcy. Cross–sectionally, our results support these predictions, but our findings differ across large and small firms.     

Good for one,bad for all: Determinants of individual versus systemic risk

We analyze a sample of large international banks in major advanced economies and examine the impact that bank-specific factors have on an institution's solvency risk and its contribution to systemic risk. We focus on the five categories that the Basel Committee on Banking Supervision has recently proposed as indicators of systemic importance. Our findings suggest that unstable funding is the main factor driving systemic risk. Furthermore, the combination of significant trading activities with global presence appears to exacerbate spillover risks to the global financial system. Interestingly, whereas trading activities contribute to the build-up of correlated or ‘wrong-way’ risk they help to mitigate individual solvency risk. Conversely, a decentralized approach to liquidity management seems to alleviate individual solvency risk but amplifies the transmission of financial distress across the financial system. This suggests that a macro-prudential approach to financial regulation should focus not only on scaling up micro-prudential measures but also on enabling the efficient transfer of risk between financial institutions.     

How do banks resolve firms’ financial distress? Evidence from Japan

The main purpose of this paper is to investigate how banks resolve firms?? financial distress in Japan. Our results show that distressed firms that have more unsecured bank debt are more likely to restructure debt successfully out of court. Second, private debt restructuring is conducted during the year in which a financially distressed firm would be compelled to report negative net worth because of substantial accounting losses if no debt restructuring plans were implemented. Third, firms that are already in a negative net worth situation are more likely to receive debt forgiveness and/or debt-for-equity swaps. Finally, both the 1-year-lagged total liabilities-to-assets ratio and accounting losses are positively related to the private workout level. These results suggest that banks resolve firms?? financial distress in shareholders?? and creditors?? interests. We argue that, along with bankruptcy laws, the stock exchange rules and the fact that banks are allowed to hold shares in these firms affect the resolution of firms?? financial distress.