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The purpose of this paper is to assess the significance of the Merton distance-to-default (DD) in predicting defaults for a sample of listed Indian firms.

The study uses a matched pair sample of defaulting and non-defaulting listed Indian firms. It employs two alternative statistical techniques, namely, logistic regression and multiple discriminant analysis.

The option-based DD is found to be statistically significant in predicting defaults and has a significantly negative relationship with the probability of default. The DD retains its significance even after the addition of Altman’s Z-score. This further establishes its robustness as a significant predictor of default.

The study re-establishes the utility of the Merton model in India using a simplified version of the Merton model that can be easily operationalized by practitioners, reasonably larger sample size and is done in a more recent period covering the post global financial crisis period. The findings could be valuable to banks, financial institutions, investors and managers.

Introduction: Financial failure is a concept that may arise from many internal and external factors such as operational, financial, and economic items and may incur serious losses. Over-indebtedness arising from managerial misjudgments may cause high financial distress, insufficiency, and bankruptcy. In this regard, determination of effects of capital structure decisions on financial failure risk is crucial.

Aim: The main purpose of this study is to explore the relationship between capital structure decisions and financial failure risk. For this purpose, data from Borsa İstanbul (BIST) for listed food and beverage companies for the period from 2004 to 2019 is used. Another purpose of this study is to compare the financial failure models considering capital structure theories.

Method: In the study, capital structure decisions are associated with five different financial ratios; while the financial failure risk is proxied by financial failure scores of Altman (1968), Springate (1978), Ohlson (1980), Taffler (1983), and Zmijewski (1984). Therefore, five different panel data models are used for testing these hypotheses.

Findings: The results of panel data analysis reveal that capital structure decisions have statistically significant effects on financial failure risk for all models; however, those effects vary from one financial failure model to another. Also, the results show that in the models in which financial failure risk is proxied by the Altman (1968) and Taffler (1983) scores, the aggressive financial policies increase the financial failure risk. However, regarding the models in which financial failure risk is proxied by the Springate (1978), Ohlson (1980), and Zmijewski (1984) scores, aggressive financial policies decrease the financial failure risk.

Originality of the Study: To the best of our knowledge, this chapter is original and important in terms of revealing the effects of capital structure decisions on the financial failure risk and comparing the financial failure models.

Implications: The results revealed that the risk of financial failure models represented by Altman (1968) and Taffler (1983) scores are found to be statistically stronger and more successful in meeting theoretical expectations compared to other models. Therefore, it would be more appropriate to refer Altman’s (1968) and Taffler’s (1983) financial failure models in financial failure risk measurements.

Recent research questions whether bankruptcy is the best proxy for assessing going concern since filing for bankruptcy is not synonymous with the invalidity of the going concern assumption. Furthermore, in contrast to debtor‐oriented countries such as the USA, liquidation is the most likely outcome of corporate insolvency in creditor‐oriented countries such as the UK, Germany, Australia and New Zealand. This suggests that bankruptcy prediction models have limited use for assessing going concern in creditor‐oriented countries. This study examines the efficacy of a corporate liquidation model and a benchmark bankruptcy prediction model for assessing company liquidation. It finds that the former is more accurate in predicting company liquidations in comparison with the latter. Most importantly, Type 1 errors for the liquidation prediction model are significantly lower than for the bankruptcy prediction model, which indicates its greater efficacy as an analytical tool for assessing going concern. The results also suggest that bankruptcy prediction models might not be appropriate for assessing going concern in countries where the insolvency code is creditor‐oriented.

The purpose of this paper is to investigate the asymmetric adjustment of cash holdings in Pakistani firms for above and below target firms.

The study employs generalized method of moments (GMM) to investigate the adjustment of cash holdings.

The study found that the firms which hold cash above the optimal level of cash holdings have higher speed of adjustment than the firms which hold cash below the optimal level. Financially constrained (FC) firms also adjust their cash holdings faster than financially unconstrained (FUC) firms but high speed of downward adjustment does not remain persistent after financial constraints are controlled. Findings of this study reveal this asymmetric adjustment in above and below target firms and extend these results in FC and FUC Pakistani listed firms, respectively.

The conclusion of this study has been derived under certain limitations. There is a vast space to extend this study in different dimensions. Firms operating in capital-intensive industries may provide different results for financial constraints because their policy designing would be quite different from other firms.

This study contributes to cash holdings research in Pakistan by exploring the adjustment behavior of cash holdings across Pakistani non-financial firms using econometric modeling. Downward adjustment rate is supposed to be higher than upward adjustment rate and this rate is tested using dynamic panel data model. Similarly, it is inferred that this relationship holds for above target firms even after including the financial constraints in the presented model.

The purpose of this paper is to examine the optimal leverage ratio, speed of adjustment, and which factors contribute to achieving the target of selected telecom companies in a partial adjustment framework from 2008 to 2017. Further is to analyze the likelihood of bankruptcy of sample companies by Altman Z-Score model and to suggest which theory of capitals structure is better in explaining leverage strategies and judicious mix of debt and equity structure of the selected telecom companies.

This paper chooses a partial adjustment model and uses the generalized method of moments technique to identify the variables that influence the target leverage ratio and the factors that influence the speed at which the target leverage is adjusted. Second, the Altman Z-score model is used in this paper to research the financial status of telecom companies using financial instruments and techniques.

For Indian telecom firms, firm-specific variables such as profitability, NDTS and Z-score lead to greater debt adjustment towards optimal level target leverage. The paper also highlights new paradigms in the Indian telecom sector, stating that top market leaders such as Bharti Airtel, BSNL, Idea, Vodafone and R.com, among others, should focus on debt reduction and interest payments, as well as implement new strategies to solve the crisis and change financial policies.

It mainly focuses on firm-specific variables because the firm-specific variables affect the leverage framework. The country-specific variables are not taken into the study. These results may be unique to telecom companies due to some peculiarities existing in the telecom sector in India. Although other sectors, both national and international level, can be taken into consideration.

This paper has ramifications for corporate executives, investors and policymakers in India, for example, in terms of considering different transition costs while changing a telecom company’s financing decisions.

To the best of the authors’ knowledge, this is the first paper of its kind to look at both financial and econometric tools to assess financial performance using the Altman Z-Score model, as well as decide leverage strategies and the pace with which they can be adjusted to target leverage in the context of Indian telecom companies.

This study aims to develop benchmarks of the financial performance of contractors and a decision support tool for evaluation, selection and appointment of contractors. The financial benchmarks allow contractors to know where they are relative to the best-performing contractors, and they can then take steps to improve their own performance. The decision support tool helps clients to decide which contractor should be awarded the project.

Financial data between 2013 and 2015 of 44 Singapore-based contractors were acquired from a Singaporean public agency. Benchmarks for Z-score and financial ratios were developed. A decision tree for evaluating contractors was constructed.

This study found that between 57% and 64% of contractors stayed in the financially healthy zone from 2013 to 2015. Ratios related to financial liabilities are relatively bad compared with international standards.

The limitation is that the data is obtained from a cross-sectional survey of contractors’ financial performance in Singapore over a three-year period. Regarding the finding that ratios relating to financial liabilities are weak, the implication is that contractors need to reduce their financial liabilities to achieve a good solvency profile. Contractors may use the benchmarks to check their financial performances relative to that of their competitors. To reduce financial risks, project clients may use these benchmarks to examine contractors’ financial performance.

This study provides benchmarks for contractors and clients to examine the financial performance of contractors in Singapore. A decision tree is provided to aid clients in making decisions on which contractors to appoint.

What is the relationship between outcomes for distressed firms and the value of managerial stockholdings in those firms? The outcomes presented are: (1) Chapter 11 reorganization; (2) acquisition/merger; (3) internal turnaround Dollar value of ownership of the firm's common stock by the firm's top managers is used to distinguish between the outcomes for distressed firms which have declining performance. The likelihood of a firm ending up in a merger with or being acquired by another private firm increases with the amount of managerial wealth invested in the firm's stock. Firms whose managers are not owners are more likely to follow an internal turnaround strategy, such as cutting costs and/or selling assets. This strategy offers non‐owner managers a greater opportunity to maintain their managerial prerogatives than does a merger or an acquisition. This outcome is consistent with agency theory, which asserts that where possible, managers act in their own best interests to the detriment of the stockholders' interests. In the context of the firm, agency theory describes the situation wherein stockholders (principals) delegate responsibility for the firm's day to day affairs to managers (agents). One key issue in agency theory is risk sharing. Managers and stockholders may prefer different outcomes for the distressed firm due to their different risk preferences. Findings of the present study suggest that managerial wealth was not a predictor of Chapter 11 reorganization in bankruptcy, but the distressed firms' strategies were affected by the aggregate dollar value of a firm's stock owned by top managers.

The business world today is witnessing ever-growing disruption. This study highlights corporate social responsibility (CSR) as an effective strategy for firms in disrupted industries to consider in order to differentiate themselves and to increase their chance of survival facing disruption.

In this study, the authors test the hypotheses using a multilevel modeling (MLM) design to capture the group and intergroup effects at the industry level and at the firm level. The empirical analysis is based on a panel sample of 1,193 firms over the 10-year period from 2010 to 2019.

The empirical analysis indicates that CSR has a positive impact on corporate financial stability and the effect is especially significant for firms in disrupted industries. Further investigation suggests that this positive effect largely runs through traits of the social pillar, such as human rights, employee relations, customer protection, product responsibility and community impact. The results are robust after controlling for other firm-specific characteristics and after addressing endogeneity concerns.

This study examines whether, and through which channel, CSR helps enhance corporate financial stability and mitigate bankruptcy risk in disrupted industries. To the best of the authors' knowledge, this study is the first attempt to explore the use of CSR as an effective strategic response to disruption. Further analysis indicates that the social capital built through CSR plays an important role in helping enhance corporate financial stability.

Purpose – We investigate the impact of CEO turnover on performance and accounting-based outcomes following major business restructurings.

Design/Methodology/Approach – We analyze a sample of 217 major operational restructurings during the period 1999–2007 using regressions and other statistical tests.

Findings – We document significant improvements in postrestructuring operating and investment efficiencies with little differentiation between restructurings that involve a change in CEO and those that involve continuing CEOs. However, we find evidence of lower accounting quality for the continuing CEO firms. First, restructuring charges of CEO turnover firms are associated with lower current period unexpected core earnings and higher future period unexpected core earnings (lower levels of classification shifting). Second, CEO turnover firms have a significantly lower percentage of (i) restructuring charge reversals and (ii) prereversal shortfalls (in meeting analyst forecast estimates) followed by reversals (suggesting lower levels of subsequent earnings management). Therefore, turnover CEOs are less likely to manipulate restructuring charges to mask true economic performance than continuing CEOs. Overall, our evidence suggests continuing CEOs undertake less substantial restructurings, while opportunistically reporting similar charges and performance improvements, consistent with attempts to pool with new CEO hires to keep their jobs.

Originality/Value – Overall, our results highlight the key economic role played by top corporate managers in major business restructurings, suggesting that CEO turnover leads to both real changes in managerial actions and altered reporting incentives.

The purpose of the authors’ research study is to identify the impact of life cycle stage on firm acquisitions.

The authors use a series of empirical databases to identify characteristics of acquirers and their targets. The authors then use logistic regressions and joint tests to identify significant differences between declining and non-declining acquirers.

The authors find that declining acquirers are more likely to pursue diversifying acquisitions and to pay for the acquisition with stock considerations. Acquisitions by declining acquirers result in positive abnormal returns initially, but post-acquisition returns are negative.

The authors’ primary limitation is their data, which only includes public acquirers and targets, and runs from January 1, 1988 to December 31, 2010.

The authors’ research suggests that regulators, stakeholders and prospective stakeholders should consider the life cycle stage of an acquiring firm in setting expectations about motivations for and likely performance subsequent to the acquisition.

The authors’ paper is the first to consider the effect of firm life cycle stage on the motivation and subsequent success of an acquisition. Given the tremendous impact to shareholders of such significant transactions, understanding the acquisition process more completely is important to capital markets participants.