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Commercial and Islamic banks are important players in the UAE financial market. However, little is known about their financial distress because these financial institutions usually resolve financial distress within their own organisations, which means that outsiders cannot explicitly observe distress. The purpose of the research is therefore to identify the main drivers of financial institutions' financial distress.

The paper estimates a probability distress prediction model using the BankScope Database and the annual reports of UAE financial institutions submitted to UAE Security Exchange Authority. The paper also analyses the impact of macroeconomic information for forecasting financial institutions' financial distress.

The fundamentals of financial institutions in terms of cost income ratio, equity to total assets, total asset growth and ratio of loan loss reserve to gross loans (all these variables with a lag of one year) positively impacted the probability of financial distress in the next year. Recent findings for emerging economies have cast some doubt on the usefulness of macroeconomic information for financial institutions' risk assessment. Similar results are found for UAE financial institutions in predicting the probability of financial distress.

This is the first study to provide empirical evidence on the drivers of financial distress of commercial and Islamic banks in UAE during 2000‐2008, and to examine the extent of the financial distress that can be can be attributed to internal bank‐specific fundamental factors and external factors in the economy.

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.

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.

This paper aims to improve the debate linking the business models of banks to their riskiness by checking if diversification exerts different impacts on the probability of bank distress depending on the level of capital buffers.

The paper focuses on a sample of listed bank holding companies observed between 2007:Q3 and 2022:Q4. The authors use three subindexes of bank diversification. The authors estimate a dynamic model specification using a system generalized method of moments with robust standard errors and consistent estimators under heteroskedasticity and autocorrelation within a panel. Sensitivity and robustness checks are performed.

Asset and income diversification increase the probability of distress in low-capitalized banks during normal periods (excluding periods of crises and high uncertainty). Concerning crisis periods, a marginal increase in asset diversification during the global financial crisis (GFC) and the COVID-19 pandemic crisis induces a more important increase in the probability of failure of well-capitalized banks relative to low-capitalized ones. Contrary to the results obtained for the GFC period, well-capitalized banks were found to pursue more careful funding diversification in reaction to the sudden increase of uncertainty during the Russia–Ukraine war.

Prudential supervision should concentrate on well-capitalized banks to encompass unexpected excessive risk-taking during crisis periods. Regulatory requirements should constrain fragile banks to avoid pursuing assets and income diversification strategies that increase earnings volatility.

The main originality of this paper is to consider the interaction between three different dimensions of bank diversification and capital regulation during stable and unstable periods using the marginal effect analysis. Moreover, this paper uses, initially, the GFC as the reference crisis period to study the impact of capital buffers and diversification interactions on the probability of bank distress. Then, the authors extend the observation period until 2022:Q4 to include two additional major events, namely, the COVID-19 pandemic and the Russia-Ukraine war.

This paper investigates the financial risk factors associated with fiscal distress in local governments. We hypothesize that fiscal distress is positively correlated with revenue concentration and debt usage, while negatively correlated with administrative costs and entity resources. The regression model results in a prediction of the likelihood of fiscal distress, which correctly classifies up to 91% of the sample as fiscally distressed or not. The model also allows for an analysis of the impact of a change in a risk factor on the likelihood of fiscal distress. A decrease in intergovernmental revenues as a percent of total revenues and an increase in administrative expenditures as a percent of total expenditures have the biggest influences on reducing the likelihood of fiscal distress.

This paper aims to examine the relationship between regulation, market discipline and banking distress.

To address the empirical question put forward above, a multivariate logit model is applied to an international sample of 586 banks from 21 European countries in the period between 2000 and 2012. To give robustness to the results, different variables have been used to test the role played by market discipline and regulation as well as an alternative methodology known as duration/survival analysis.

It can be found that market discipline is a good indicator in signalling banking distress, that is, market discipline has penalized more banks with a higher likelihood of being in distress. Nonetheless, as broadly acknowledged, market discipline was not sufficient per se to avoid banking distress in Europe. With regard to regulation, this paper evidences that the adoption of other regulatory measures beyond the simple transposition of changes occurred in the EU Directives such as borrower-based measures and limits on pre-emptive exposures’ concentration, have contributed toward reducing the probability of distress of EU banks, showing that the introduction of this kind of measures was necessary and relevant. In addition, in this paper, it can be found that the NPL ratio, size, capital (including the well-known regulatory capital ratio, as well as the novel leverage ratio which discards the risk weights present in the former one) and liquidity are good indicators of banking distress which lead us to conclude that the new regulatory framework known as Basel III is on the right path to mitigate the probability that a new banking crisis similar to the last one takes place again.

The first limitation regards the period of time chosen, that is, from 2000 to 2012, empirically neglecting, to some extent the important regulatory changes occurred after the aforementioned period. Nonetheless, as mentioned in the Data and Methodology section, the period ends in 2012 because it is difficult to flag a reasonable number of banks’ bailouts afterwards, to properly run the type of model used in this paper. The second limitation is the fact that the possible changes in the risk management and risk assessment by institutions and in the behaviour of investors, acknowledge as weak and inappropriate before the on-set of the global financial crisis, albeit very relevant, are not in the scope of this paper.

Despite the welcomed changes performed by regulators so far, some aspects are not complete yet and new areas deserve more empirical work and attention by the regulators and supervisors. Some of them stem directly from the results obtained from this paper such as the enhancement and a close monitoring of the current Pillar 3 framework the increase of the adoption of more targeted tools, in a more preemptive way, to counter the build-up of risks and the implementation of the leverage ratio.

In the aftermath of the financial crisis, the identification of leading indicators signalling emerging risks to the banking system has become a major priority to central banks and supervisory authorities. As a consequence, several studies have formulated the aim of analysing predictive characteristics of a set of macroeconomic variables, such as GDP Growth, Credit-to-GDP, Inflation, M2-to-GDP, among others. Other studies take a different perspective and complement the analysis with bank-specific risk indicators. Nonetheless the aforementioned studies do not consider the relationship between regulation and market discipline and banking distress. This is the gap the authors wanted to fill, and this assessment is the main contribution of this paper.

The purpose of this study is to empirically examine how the voluntary formation of a specialised investment committee (IC) and IC characteristics affect financial distress risk (FDR) and whether such impact is influenced by the level of investment inefficiency.

The authors use a large sample of Gulf Cooperation Council (GCC) non-financial companies during 2006–2016. A principal component analysis is done to aggregate and derive a factor score for IC characteristics (i.e. independence, size and meeting) as a proxy for the effectiveness of IC. This study also uses three measurements of FDR to corroborate the findings and partitions sample firms into overinvesting and underinvesting companies to examine the potential impact of investment inefficiency on the IC–FDR nexus.

Using feasible generalised least square estimation method, the authors document that the likelihood of financial distress occurrence decreases for firms with separate ICs. The authors also find that firms with effective ICs enjoy lower FDR. In other words, the probability of financial distress minimises if the IC is large, meets frequently and has a high number of independent directors. However, the authors find neither any moderation nor any mediation effect of investment inefficiency for the impact of IC and IC attributes on FDR. The additional analysis indicates the expected benefits of an actively performing IC are amplified for firms with risk of both over- and underinvestment. These findings are robust to alternative measures of FDR and investment inefficiency, sub-sample analysis and endogeneity concerns.

This study, to the best of researchers’ knowledge, is the first to provide evidence in GCC firms’ perspective, suggesting that the existence of an effective IC is associated with a lower risk of financial distress, and to some extent, the economic benefits of IC are aggrandised for companies with a high probability of over- and underinvestment problems. These results are unique and contribute to a small but growing body of literature documenting the need for effective ICs and their economic consequences on investment efficiency in the FDR environment. The findings of this study carry valuable practical implications for regulatory bodies, policymakers, investors and other interested parties in the GCC region.

This paper aims to develop a corporate financial distress model for Indian listed companies using financial and non-financial parameters by using a conditional logit regression technique.

This study used a sample of 96 companies, of which 48 were declared sick between 2014 and 2016. The sample was divided into a training sample and a testing sample. The variables for the study included nine financial variables and four non-financial variables. The models were developed using financial variables alone as well as combining financial and non-financial variables. The performance of the test sample was measured with confusion matrix, sensitivity, specificity, precision, F-measure, Types 1 and 2 error.

The results show that models with financial variables had a prediction accuracy of 85.19 and 86.11 per cent, whereas models with a combination of financial and non-financial variables predict with comparatively better accuracy of 89.81 and 91.67 per cent. Net asset value, long-term debt–equity ratio, return on investment, retention ratio, age, promoters holdings pledged and institutional holdings are the critical financial and non-financial predictors of financial distress.

This study contributes to the financial distress prediction literature in different ways. First, there have been, until now, few studies in the area of financial distress prediction in the Indian context. Second, business failure studies in the past have used only financial variables. The authors have combined financial and non-financial variables in their model to increase predictive ability. Thirdly, in most earlier studies, variable institutional holdings were found to affect financial distress negatively. In contrast, the authors found this parameter to be positively significant to the financial distress of the company. Finally, there have hitherto been few studies that have used promoter holdings pledged (PHP) or pledge ratio. The authors found this variable to influence business failure positively.

This paper uses survival analysis to investigate fiscal distress in special district governments. We hypothesize that fiscal distress is positively correlated with revenue concentration and debt usage, and negatively correlated with organizational slack and entity resources. Our model addresses differences in district functions, financing and legislation. Our regression model predicts the likelihood of fiscal distress and correctly classifies 93.4 percent of the districts as fiscally distressed or not. The results show that the most important indicator of fiscal distress is a low level of capital expenditures relative to total revenues and bond proceeds. The information needed to predict fiscal distress is publicly available, making our model useful in the prevention, detection, and mitigation of fiscal distress in U.S. districts.

Personal financial stress-free living is desired by many, which dwells on sound financial literacy (including financial behaviour, financial knowledge and financial attitude). Many individuals do not make optimal savings and investment decisions. The realisation that these choices may well lead to low living standards has also increased economic anxiety, especially in Sub-Sahara African countries, including Ghana. Thus, this study underscores the link between financial literacy and financial distress in Ghana. It establishes whether persons that are financially literate escape financial distress in their life.

The paper engages nationally representative survey data and adopts a positivist research approach with logistic regression analysis to establish the likelihood of financial literate persons experiencing financial distress.

This study establishes that financially literate individuals are 2.4% less likely to experience financial distress. Socioeconomic characteristics greatly influence the probability of one experiencing financial hardship. It submits that policy can be directed towards improving financial habits (financial literacy) to enhance individuals' financial behaviour to lessen personal financial distress.

Not much attention has been paid to whether financial literacy has a nexus with financial distress. Few studies (not on Sub-Saharan Africa) that have looked at this are done, neglecting a sensitivity analysis of socioeconomic characteristics in establishing the relations. However, this current study dwells on econometric analysis to establish the margin or extend to which a financially literate person may or may not escape financial distress given his/her socioeconomic characteristics.