Bankrupt Firms Research Articles

The Effect of Going-Concern Opinion Reliability on Market Prices

Large unexpected corporate failures associated with the global financial crisis heightened investors’ and regulators’ concerns about the diagnosticity of auditors’ going-concern opinions. Consistent with these concerns, extant research indicates that going-concern opinions are only moderately diagnostic at best, with only fifty to sixty percent of financially distressed firms receiving going-concern audit opinions prior to bankruptcy. Using an experimental market, we show that under conditions of moderate diagnosticity, investors discount the going-concern signal. Compared to a market with high diagnosticity, investors penalize the stock prices of non-bankrupt firms and fail to adequately discount the prices of bankrupt firms, even in instances when the going-concern signal accurately predicted the bankruptcy outcome. Interestingly, we find that a market with moderately diagnostic going-concern opinions provides no greater informational value than a market without going-concern opinions altogether. Specifically, we demonstrate that stock price behavior and, in turn, average investor earnings are no different in a market with moderate diagnosticity as compared to a market that lacks any going-concern signal. These findings have implications for regulators who are interested in improving the quality of going-concern opinions.

Post-Communist Capitalism and the Modern World of Dead Economy

After the collapse of the Communist regimes and their command economies, the countries of the former Soviet Union found themselves with only a very small amount of goods to supply to the global market. There was no way that they could have existed in an economy of this type that is nothing more than a corpse or a so-called “necroeconomy.” As international experience shows, dead firms do exist and “successfully” function in the most developed of economies as well. These insolvent and, in fact, bankrupt firms which continue to operate despite their “mortality” are commonly referred to as “zombie-firms.”

Evaluating Predictive power of Data Envelopment Analysis Technique Compared with Logit and Probit Models in Predicting Corporate Bankruptcy

Simultaneous with extensive environmental changes and the rapid development of technology which has increasingly accelerated economy, competitiveness economical enterprises have restricted earning profit and make probable closing of bankrupt firms. Thus it seems necessary to find a model that can predict financial crisis and bankruptcy of companies. Nowadays occurrence of significant progress in other sciences, such as computer and math attract the attention of the financial scholars toward designing and using more exact patterns like Data Envelopment Analysis (DEA). For this purpose, this study uses DEA technique to predict the bankruptcy likelihood of manufacturing firms and also compare its predictability with2 methods : Logit and Probit models. Study sample includes all manufacturing firms listed in Stock Exchange of Tehran from 2000-2010. The results showed that the accuracy of the designed model under DEA technique is %72 and the predictability of Logit and Probit models has been81, and %80 respectively. The results also showed DEA was proved to be an effective tool for predicting bankruptcy likelihood of manufacturing firms; but,it acted less efficient than Logit and Probit models.

Reorganization of Bankrupt Firms in France Continuation Versus Sale

One particularity of the French bankruptcy law is that it provides bankrupt rms with two forms of reorganization. The Court may order either the continuation of the bankrupt firm in the same entity or the sale of the bankrupt firm to another entity as going-concern. The purpose of this paper consists in investigating the factors that would influence the reorganization outcome in France (continuation or sale). We use a random sample of 500 firms that led for reorganization in the commercial Court of Paris between 1995 and 2004 and that had their reorganization plans confirmed between May 1995 and September 2006. Logistic regression analysis shows that the probability of confirming a continuation plan increases with the profitability of the firm, the fraction of intangible assets and for firms having financing and/or business problems whereas the probability of confirming a sales plan increases with the size of thebankrupt firm, the secured debt to assets ratio and for debtors having personal problems.

Pricing Expected Deviations from Absolute Priority in Bankruptcy

We estimate pre-bankruptcy shareholders’ expected negotiating power using accounting information available at the bankruptcy filing. We find that the equity value on the day following the bankruptcy filing reflects theoretical determinants of priority violations. Specifically, the post-petition value of pre-bankruptcy shareholders’ claims on the bankrupt firms’ assets is positively related to the ratio of unsecured-to-secured debt, tax-loss-carry-forwards, and intangible asset value which would be lost in liquidation. Our results further suggest that the option to put leased assets back to the lessor increases shareholder power. Our results are (a) significant after controlling for firm size, financial health, and the likelihood of emergence; (b) not driven by multicollinearity in explanatory variables; and (c) robust to variation in post-bankruptcy equity valuation date.

Provision of Incentives in Chapter 11 Firms

This paper examines the use of key employee retention and incentive plans (KERPs) in bankrupt firms. We find that firms in Chapter 11 are more likely to offer KERPs when firms are located in thicker employment markets, when creditors have strong control, and when bankrupt firms have complex operations and claim structures. Newly hired turnaround specialists are more likely to be covered by KERPs than incumbent CEOs. Objectives set by incentive plans are strongly linked to the probability of emergence. Our results suggest that KERPs are an efficient contracting solution to the problem of retaining and incentivizing key employees in bankruptcy.

Is Chapter 11 Efficient?

The efficiency of the Chapter 11 bankruptcy process is examined by estimating the impact of Chapter 11 filings on the operating performance of bankrupt firms. We control for firm‐level heterogeneity in prefiling characteristics using matching methods to select benchmark firms comparable to filing firms. We compare bankrupt firms’ operating performances with those of matched nonbankrupt firms. Our results challenge the contention that Chapter 11 is an inefficient, debtor‐friendly mechanism that rehabilitates economically nonviable firms. We demonstrate that firms that file under Chapter 11 perform no worse and, if anything, better than comparable nonfiling firms.

Evaluating Firms In Financial Distress: An Event History Analysis

<span>This study uses event history methodology and dynamic models to examine bankruptcy and financial distress. Dynamic models incorporate the conditional probability of a firms financial status changing from financially distressed to stable or bankrupt and enable us to simultaneously examine stable, financially distressed and bankrupt firms. We also add to the literature by incorporating two economic indicator variables and extend prior research with an analysis by industry segment.</span>

A Chaos Approach To Bankruptcy Prediction

<span>Chaotic systems, although deterministic and predictable over short horizons, appear to be random. This study applied chaos theory to bankruptcy prediction using a pair-matched sample of bankrupt firms. Given that healthy systems exhibit more chaos than unhealthy ones, it was hypothesized that the returns of firms nearing bankruptcy would exhibit significantly less chaos, measured with Lyapunov exponents, than at an earlier period. Successful univariate and multivariate bankruptcy prediction models were then constructed using the obtained Lyapunov exponents.</span>

HYBRID GENETIC PROGRAMMING-BASED SEARCH ALGORITHMS FOR ENTERPRISE BANKRUPTCY PREDICTION

Bankruptcy is an extremely significant worldwide problem that affects the economic well- being of all countries. The high social costs incurred by various stakeholders associated with bankrupt firms imply the need to search for better theoretical understanding and prediction quality. The main objective of this paper is to apply genetic programming with orthogonal least squares (GP/OLS) and with simulated annealing (GP/SA) algorithms to build models for bankruptcy prediction. Utilizing the hybrid GP/OLS and GP/SA techniques, generalized relationships are obtained to classify samples of 136 bankrupt and nonbankrupt Iranian corporations based on financial ratios. Another important contribution of this paper is to identify the effective predictive financial ratios based on an extensive bankruptcy prediction literature review and a sequential feature selection (SFS) analysis. A comparative study on the classification accuracy of the GP/OLS- and GP/SA-based models is also conducted. The observed agreement between the predictions and the actual values indicates that the proposed models effectively estimate any enterprise with regard to the aspect of bankruptcy. According to the results, the proposed GP/SA model has better performance than the GP/OLS model in bankruptcy prediction.

Bankruptcy and the Collateral Channel

ABSTRACTDo bankrupt firms impose negative externalities on their nonbankrupt competitors? We propose and analyze a collateral channel in which a firm's bankruptcy reduces the collateral value of other industry participants, thereby increasing their cost of debt financing. We identify the collateral channel using novel data of secured debt tranches issued by U.S. airlines that include detailed descriptions of the underlying collateral pools. Our estimates suggest that industry bankruptcies have a sizeable impact on the cost of debt financing of other industry participants. We discuss how the collateral channel may lead to contagion effects that amplify the business cycle during industry downturns.

'Zombie' Banks Make 'Zombie' Firms

This paper finds evidence that regulatory forbearance toward weakly capitalized banks, which creates “zombie” banks, leads to the creation of “zombie” firms in the Japanese banking crisis of 1997-2003. Capital weak banks bankrupt large borrowers at higher levels of indebtedness than similar firms with better capitalized banks. The average “zombie” entering bankruptcy has an extra 4.7 years of unlife and is 20.8% more indebted than bankrupt firms with better capitalized banks. This is the first direct evidence of bank capitalization being the driving force behind “zombie” firms. I quantify the direct costs of increased bad debts due to forbearance at 4.2% of nominal Japanese GDP in 1997 or US$181 billion. This does not include the indirect costs such as the loss to competitors through lower profitability and employment, nor the foregone profits for banks of not making loans to profitable firms. The results are robust to several alternative measures of indebtedness and are confirmed by robustness checks showing that weakly capitalized banks increase the rate of bad loan disposal and bankruptcies of listed firms after receiving government capital injections. These results are particularly relevant in the aftermath of the global financial crisis of 2008. Regulatory forbearance towards banks remains a politically more palatable option than extensive capital injection in many countries; this study suggests that forbearance may prove to be very costly.

Bad News Do Not Always Travel Slowly: The Bankruptcy Case

This paper tests to what extent the Hong and Stein (1999) model explains the stock price performance of firms filing for Chapter 11 bankruptcy. In line with the model’s main prediction, I find that the market severely misprices (correctly prices) the bankrupt firms for which information is likely to diffuse slowly (rapidly) across investors. My key finding is robust to a range of alternative methods for adjusting for risk and different periods for computing the abnormal stock returns. My innovative framework provides an acid test of the predictive ability of the Hong and Stein (1999) model, with my results suggesting that it offers important insight into the workings of financial markets, even in the very extreme setting I consider.

DEA as a tool for predicting corporate failure and success: A case of bankruptcy assessment

Using an additive super-efficiency data envelopment analysis (DEA) model, this paper develops a new assessment index based on two frontiers for predicting corporate failure and success. The proposed approach is applied to a random sample of 1001 firms, which is composed of 50 large US bankrupt firms randomly selected from Altman's bankruptcy database and 901 healthy matching firms. This sample represents the largest firms that went bankrupt over the period 1991–2004 and represents a full spectrum of industries. Our findings demonstrate that the DEA model is relatively weak in predicting corporate failures compared to healthy firm predictions, and the assessment index improves this weakness by giving the decision maker various options to achieve different precision levels of bankrupt, non-bankrupt, and total predictions.

Impact of professional fees on performance of firms undergoing reorganisation in Chapter 11

There has been wide spread belief in finance and legal literature and popular press that costs related to reorganisation under bankruptcy mechanism are excessive. Using a sample of 76 firms that filed for bankruptcies under Chapter 11 between January 1999 and December 2003, this paper examines the impact of direct costs on firm performance over the Chapter 11 period. Our sample firms have median direct costs equal to 2.83% of the firms’ pre-filing sales, similar to the direct costs reported in other studies. Consistent with our hypothesis that professionals employed by bankrupt firms help to make these firms better operational decisions, we find professional fees to be positively related to improvement in firm performance. We also observe negative relationships between changes in firm performance and time spent in Chapter 11 as well as utilisation of pre-pack mode of bankruptcy.

CORPORATE DIVERSIFICATION, BUREAUCRATIC COSTS AND LIKELIHOOD OF BANKRUPTCY

Based on a sample of 858 observations, we show that there is a significant difference between the bureaucratic costs incurred by bankrupt and non-bankrupt firms. Further, our results from matched-p...

Restructuring and Post Emergence Performance of Bankrupt Firms: Evidence from the Post 1991 Period

Restructuring and Post Emergence Performance of Bankrupt Firms: Evidence from the Post 1991 Period

RICH LANGUAGE FOR POOR FIRMS: THE SYMBOLIC MANAGEMENT OF BANKRUPTCY

While recent research has documented how firms effectively use language and appearance to manage audience reactions to major corporate activities, little is known about the potential for bankrupt firms to employ such symbolic management strategies. Moreover, the specific elements of symbolic management have been under-theorized. This study addresses both of these issues by theorizing and testing the notion that firms that engage in symbolic management across four key questions (why, who, how, and what) can generate positive bankruptcy outcomes. Specifically, we hypothesize and find that that bankrupt companies can mitigate bankruptcy’s stigma by i) strategically attributing blame for their failure, ii) publicly acknowledging their alignment with and concern for crucial external stakeholders, iii) proffering specific plans to address their organization’s weaknesses, and iv) framing the bankruptcy as a deliberately chosen strategic opportunity. We argue that these sense-giving strategies can be effective in accentuating management’s competence and control over the organization’s fate, thus making crucial audiences more inclined to continue supporting the organization post-filing. We test our hypothesis with data on 250 bankruptcy cases spanning three years, employing a careful content analysis of these companies’ rich language surrounding the bankruptcy filing. Our supportive results highlight the importance of active impression management for bankrupt firms, adding to our knowledge of symbolic management and the bankruptcy process.

Building Legal Indexes to Explain Recovery Rates: An Analysis of the French and UK Bankruptcy Codes

In this paper, we test the characteristics of bankruptcy procedures that are likely to generate recoveries for the creditors. Such recoveries are related to the performance of bankruptcy law as they stem from the procedures’ ability to preserve the value of bankrupt firms, as basis of creditors’ repayment. We give elements of answer by taking into consideration two countries that are good representatives of the two main legal systems prevailing in Europe: France (Civil Law) and United Kingdom (Common Law).In order to identify the characteristics of bankruptcy procedures that generate recoveries, we build 132 original legal indexes accounting for the main functions of bankruptcy law that were highlighted initially by Hart (2000). Namely, we measure the accessibility of the procedure, their ability to disclose public information, the level of protection of the debtor’s assets, the coordination of the claimants and their decision power under bankruptcy, and the sanction of faulty management. We show that the French procedures are more protective of the debtor’s assets and favor more the coordination of claims. In United-Kingdom, we find strong opposition between the liquidation and the reorganization procedures: the former ones prioritize the protection of secured claims, while unsecured creditors benefit from higher decision power under the latter ones.We then use an original database of 833 French and UK bankrupt SMEs to measure the recovery rates that are generated by each procedure. By controlling for the value of assets, the structure of claims, the origins of default, and the firm characteristics, we first isolate the bankruptcy rules that are associated to higher recovery rates: namely, accessibility of the procedure, protection of the debtor’s assets, protection and coordination of claims. On the contrary, information disclosure under bankruptcy has negative impact on total recoveries, probably due to the breach in confidentiality. Last, some bankruptcy rules are not significantly related to recoveries, especially the severity towards faulty management.

Bankruptcy risk model and empirical tests

We analyze the size dependence and temporal stability of firm bankruptcy risk in the US economy by applying Zipf scaling techniques. We focus on a single risk factor--the debt-to-asset ratio R--in order to study the stability of the Zipf distribution of R over time. We find that the Zipf exponent increases during market crashes, implying that firms go bankrupt with larger values of R. Based on the Zipf analysis, we employ Bayes's theorem and relate the conditional probability that a bankrupt firm has a ratio R with the conditional probability of bankruptcy for a firm with a given R value. For 2,737 bankrupt firms, we demonstrate size dependence in assets change during the bankruptcy proceedings. Prepetition firm assets and petition firm assets follow Zipf distributions but with different exponents, meaning that firms with smaller assets adjust their assets more than firms with larger assets during the bankruptcy process. We compare bankrupt firms with nonbankrupt firms by analyzing the assets and liabilities of two large subsets of the US economy: 2,545 Nasdaq members and 1,680 New York Stock Exchange (NYSE) members. We find that both assets and liabilities follow a Pareto distribution. The finding is not a trivial consequence of the Zipf scaling relationship of firm size quantified by employees--although the market capitalization of Nasdaq stocks follows a Pareto distribution, the same distribution does not describe NYSE stocks. We propose a coupled Simon model that simultaneously evolves both assets and debt with the possibility of bankruptcy, and we also consider the possibility of firm mergers.