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This study aims to develop a model based on the financial variables for better accuracy of financial distress prediction on the sample of private French, Spanish and Italian firms. Thus, firms in financial difficulties could timely request for troubled debt restructuring (TDR) to continue business.

This study used a sample of 312 distressed and 312 non-distressed firms. It includes 60 French, 21 Spanish and 231 Italian firms in both distressed and non-distressed groups. The data are extracted from the ORBIS database. First, the authors develop a new model by replacing a ratio in the original Z”-Score model specifically for financial distress prediction and estimate its coefficients based on linear discriminant analysis (LDA). Second, using the modified Z”-Score model, the authors develop a firm TDR probability index for distressed and non-distressed firms based on the logistic regression model.

The new model (modified Z”-Score), specifically for financial distress prediction, represents higher prediction accuracy. Moreover, the firm TDR probability index accurately depicts the probabilities trend for both groups of distressed and non-distressed firms.

The findings of this study are conclusive. However, the sample size is small. Therefore, further studies could extend the application of the prediction model developed in this study to all the EU countries.

This study has important practical implications. This study responds to the EU directive call by developing the financial distress prediction model to allow debtors to do timely debt restructuring and thus continue their businesses. Therefore, this study could be useful for practitioners and firm stakeholders, such as banks and other creditors, and investors.

This study significantly contributes to the literature in several ways. First, this study develops a model for predicting financial distress based on the argument that corporate bankruptcy and financial distress are distinct events. However, the original Z”-Score model is intended for failure prediction. Moreover, the recent literature suggests modifying and extending the prediction models. Second, the new model is tested using a sample of firms from three countries that share similarities in their TDR laws.

The purpose of this paper is to extend the current literature on corporate asset writedowns.

The paper explains the anomalous price responses to asset writedowns by examining both stock and bond price responses. It applies bond and stock event study methodologies using daily prices. Firms are analyzed by partitioning them according to their financial viability. This analysis is based on the logic that it is more difficult to assess the prospects of firms in financial difficulty from publicly available information.

The study reveals that while asset writedowns have no information content for stockholders of healthy firms, stockholders of financial distressed firms suffer a significant adverse effect. This differential stock price reaction provides an explanation for the anomalous results reported in previous studies. Similar price responses are found for bondholders. The results indicate that the market interprets an asset writedown announcement by a financially distressed firm as a strong negative signal about the firm's prospects. It is also found that the firm's financial health, the subordination status of the bond, the bond's maturity, the bond rating, the amount of the write‐off undertaken by a firm in distress, and the leverage change experienced by the firm are all important determinants to bond price response. Long‐run analysis reveals significant differences in performance and leverage change between healthy and financially distressed firms undertaking asset writedowns.

The paper resolves the anomalous results on information content of corporate asset writedown announcements on stockholders and bondholders. Broadly, the findings have important implications for both finance and accounting literatures in terms of semi‐strong market efficiency and security market signaling issues and the importance of considering financial viability of firms when testing market efficiency in the presence of publicly available information.

This is the first study to address this issue by examining the information content of asset writedown announcements for both stockholders and bondholders. Past studies document a significant negative stock price response to asset writedown announcements, while there is no bond price response to such official acknowledgment of asset impairment.

This paper aims to examine the empirical relationship between firm-level characteristics and the variability of the average portfolio returns of distressed firms. The cross-sectional role of momentum in the market mispricing of distressed firms is evaluated. Distress risk associated with size and book-to-market ratio is also disentangled.

All of NYSE, AMEX and NASDAQ stocks between January 1972 and December 2008 are used, and the individual and joint role of firm characteristics are studied in detail. Using a measure of distressed stocks based on Campbell, Hilscher and Szilagyi (CHS, 2008), new findings on how stock return anomalies are related to the interactions between firm characteristics and financial distress risk are provided.

The findings show that the size and value effects are not due to distress risk. Also, contrary to the existing empirical evidence, momentum does not proxy for distress risk. Furthermore, in the cross-sectional analysis, momentum subsumes the effect of size risk, and book-to-market acts as an independent state variable.

The exposition of the paper is limited in many directions. To measure the extent of financial distress, only the model of CHS (2008) is used. As the level of distress is the key input in the paper, it would be interesting to use some other measure of distress, such as Z-score and O-score in the sample.

Collectively, the pricing results in this paper help to foster a better understanding of the nature of distressed stocks, and the identification of distress risk premium. It will help scholars and investment professionals to make robust portfolio management decisions.

Overall, this paper investigates an important research direction that can potentially shed new light on our understanding of the risk–return relationship of financially distressed stocks. The individual effect of momentum on the variability of the distressed firm’s average returns is highlighted. A formal cross-sectional test of the relationship between distress risk and firm characteristics that include momentum is presented. None of them is quite known in the existing literature.

This paper examines the relation between takeover likelihood and the documented underperformance of distressed company stocks while exploring two competing hypotheses. The failure risk explanation predicts lower returns to distressed firms with high probability of being acquired because the acquisition reduces risk and investors' required return. Conversely, the agency conflicts explanation predicts lower returns when acquisition is unlikely.

The likelihood of receiving a takeover bid is estimated, and portfolio tests explore the underperformance of distressed company stocks relative to non-distressed stocks across varying levels of takeover likelihood. Predictive regressions subsequently examine the relation between distress, takeover exposure and future firm operating performance including how the relation is affected by state anti-takeover laws.

Distressed stocks underperform non-distressed company stocks by economically and statistically significant margins when takeover likelihood is low, yet there is no evidence of underperformance among distressed stocks with moderate or high takeover exposure. Consistent with agency conflicts playing a key role, distressed firms that are disciplined by takeover threats invest more, use more leverage and experience higher future profitability. State-level anti-takeover legislation limits this disciplinary effect, however.

The results show that the well-documented distress anomaly is driven by a subset of distressed firms whose managers face limited pressure from the external takeover market. The evidence casts doubt on the failure risk explanation and suggests that agency conflicts play a key role.

Major crises such as the global financial crisis 2007–08 or the COVID-19 crisis increase the level and likelihood of supplier financial distress. This research expands the understanding of how cooperatively, respectively, uncooperatively buying firms might respond to suppliers who suffer from financial distress in the course of major crises.

The authors build on a collaborative project with a German automotive OEM, analyze OEM internal “financial quick check data”, questionnaire data and longitudinal supplier financial data and apply regression, mediation and difference-in-difference estimation analyses.

The results show that the stronger the dependence on the distressed supplier, the more cooperative the buying firm's response. Furthermore, a more cooperative response of the buying firm has a strong positive influence on the suppliers' financial performance and hence recovery from the distress situation. Insights from supplier financial distress in the course of the financial crisis 2007–2008 can serve as learnings for the COVID-19 crisis.

The study fills a gap in the scholarly literature on “response to risk incidents” and response formation. Resource dependence theory and resource dependence dynamics offer a strong rationale for the type of response buying firms are likely to choose.

Besides offering the first menu of response options, this study can help practitioners in figuring out the most appropriate response to distressed suppliers. The findings can assist buying firms in their decisions how to deal with suppliers during major economic and financial crises.

This research is the first to conceptualize buying firms' response options to financially distressed suppliers, to investigate the influence of dependence on buying firm's response and to reveal the consequences of the buying firm's response for the supplier's financial recovery.

Previous research found that customer financial distress can spillover to supplier firm decisions. The aim of this paper is to examine the investment decisions of suppliers of financially distressed customers.

The paper uses a US sample of customer-supplier relationships from Compustat Segments between 1980 and 2017. The author uses a linear probability model in the baseline regression analysis. To ensure robustness, a logit regression model and an instrumental variable estimation approach are used, instrumenting for distress at the customer level using a negative shock to customer industry demand.

This study finds suppliers are more likely to reduce their investment in Capex when a customer is financially distressed. Supplier investment efficiency does not improve when a customer is financially distressed as suppliers with a greater likelihood of under-investment reduce their investment, while suppliers with a greater likelihood of over-investment increase their investment. The effect of customer distress on supplier investment decisions is more pronounced for suppliers of economically distressed customers.

This paper examines how suppliers adjust their investment in response to customer distress, providing an additional channel through which customer distress affects suppliers. Overall, this study finds an important real implication of financial distress in the buyer-supplier relationship.

The purpose of this study is to examine the impact of financial distress (FD) on investment-cash flow sensitivity (ICFS) of Indian firms.

The study uses the system generalized method of moments (GMM) technique to investigate the effect of FD on ICFS of Indian firms during the period from 2001 to 2019.

Using FD measures like Ohlson's bankruptcy method, Altman's Z-score model and financial-distress ratio, the researchers find that FD increases ICFS and negatively affects corporate investment. The researchers’ findings explain that FD increases restrictions on external financing, which makes cash flow more important for corporate investment. Additionally, the researchers find that the effects of FD on ICFS are weak (strong) for bigger and group affiliated (smaller and standalone) firms. The study’s findings are robust to several measures of FD, group affiliation and firm size.

First, the researchers find that FD affects the ICFS, therefore, financially distressed firms should have sufficient internal funds or external funds for investment. Second, lending agencies should also consider the firms' FD condition before providing funds to secure their money. Third, investors should be very careful while investing in a financially distressed firm as we find that financially distressed firms face a decline in their investment which might reduce firm profitability.

This study contributes to the existing literature by providing empirical evidence by analyzing the impact of FD on ICFS in the context of India. As per the authors’ knowledge, this is the first-ever attempt to examine the effect of FD on ICFS.

The purpose of this paper is to identify financial characteristics that assess and predict corporate financial distress in publicly traded firms quoted in the London Stock Exchange.

The model incorporates three existing literatures as an alternative to bankruptcy. The model has two stages: the first stage discriminates financially healthy or distressed firms utilizing binary logit regression. The second stage makes use of the univariate analysis. Firms can be further categorized into four possible outcomes: financially healthy, potentially healthy targets and financially distressed and potentially distressed acquisition targets.

It was found that financial distress could be identified as early as three years prior to the event. Moreover, statistically significant differences were found between the four firm sample groups.

The vast changing environment and the financial crisis highlight the need for future research on the world trade implications, as well as the individual macroeconomic variables of each country.

This is the first time a UK study makes use of this model in order to follow the hazard model's procedure based on recent financial data. Due to the scope of the analysis, a new version of the latter procedure is employed. A further innovation that makes the model unique is its ability to classify a firm into one of several a priori groupings according to the latter's individual characteristics. This overcomes the limitation of earlier studies that only considered two possible outcomes for firms.

This paper aims to examine whether financially distressed firms manipulate core or operating income through the misclassification of operating expenses as income-decreasing special items.

This sample comprises firms in the USA with data from 1989 to 2010. The authors used the methodology given in McVay (2006) and multiple regressions.

Managers of financially distressed firms are more likely to inflate core or operating income as compared to the healthy firms to meet or beat earnings benchmarks. They do so by misclassifying core or operating expenses as income-decreasing special items. Specifically, core expenses are shifted to income-decreasing special items like goodwill impairments, settlement costs, restructuring costs and write downs.

The paper sheds light on an important firm characteristic, financial distress that intensifies classification shifting – an earnings management tool which auditors, investors and regulators find tough to detect. The findings have implications for investors, as they fail to comprehend such shifting (McVay, 2006); analysts, who issue forecasts based on street earnings; lenders, as distressed firms may be concealing their true performance; and regulators, as the misclassification of income statement items is a violation of accounting principles.

The authors extend the literature on accruals and real earnings management by the financially troubled firms and present first evidence that the managers of such firms also manipulate core or operating income through classification shifting.

Relationships between corporate governance characteristics and financial distress status are examined for a sample of Canadian firms. Results from logit regression analysis of 46 financially distressed and 46 healthy firms lead us to conclude that the board of director’s composition explains financial distress, beyond an exclusive reliance on financial indicators. Additionally, supplemental results indicate that outside directors’ ownership and directorship affect the likelihood of financial distress. Furthermore, splitting financially distressed firms based on chief executive officer change as a proxy of turnaround strategies provides useful insights on corporate governance characteristics in financial distress.