Indicators Of Financial Distress Research Articles

The Impact of Ownership Structure on the Indicator of Financial Distress In Indonesian Companies

The increase in bankruptcy cases and delaying debt repayment by 16.43 percent during the year of 2015 to 2017 reinforced the importance of having good corporate governance to avoid this issue. This study aims to delve into the effect of ownership structures on the risk of financial distress in 421 companies (except financial institu-tions) in the period from 2012 to 2017. The types of ownership that are being exam-ined are Institutional Ownership, Insider Ownership, Government Ownership, and Foreign Ownership. This study uses OLS Driscoll-Kraay standard error panel data regression. The results of this study shows that Institutional Ownership has a positive relationship to financial distress which is caused by the tendency of Institutional in-vestors to conduct passive monitoring. Inversely, foreign ownership and government ownership have been proven to have a negative relationship with the risk of financial distress. This was caused by the capability of the foreign investors to do better- moni-toring activities and maintain the ultimate shareholder’s company in their home country. Furthermore, the presence of merah putih shares allows the government to have absolute voting power. This research intends to provide new business perspec-tives to companies, investors, regulators, creditors, and other stakeholders for eco-nomic decision- making purposes. Peningkatan perkara kepailitan dan penundaan kewajiban pembayaran utang sebe-sar 16.43 persen sepanjang tahun 2015-2017 menyadarkan kembali pentingnya tata kelola yang baik untuk menghindari hal tersebut. Penelitian ini mempelajari pengaruh struktur kepemilikan terhadap risiko kesulitan keuangan di perusahaan terhadap 421 perusahaan (kecuali lembaga keuangan) pada tahun 2012-2017. Jenis-jenis kepemilikan yang diteliti adalah kepemilikan institusional, kepemilikan manajerial, kepemilikan pemerintah, dan kepemilikan asing. Hal yang ditemui dari hasil penelitian ini yaitu dapat dibuktikan bahwa kepemilikan institusional memiliki hubungan positif terhadap risiko kesulitan keuangan yang disebabkan oleh kecender-ungan investor institusional untuk melakukan passive monitoring. Sebaliknya kepemilikan asing dan kepemilikan pemerintah terbukti memiliki hubungan negatif terhadap risiko kesulitan keuangan, dengan alasan kemampuan investor asing dalam melakukan kontrol dan menjaga reputasi perusahaan di negara asalnya. Sedangkan, pemerintah memiliki voting power yang bersifat mutlak dengan adanya saham merah putih. Penelitian ini bermaksud untuk memberikan perspektif baru kepada pihak-pihak yang berkepentingan untuk pengambilan keputusan ekonomi.

The Effect of Financial Distress Indicators on the Share Price of Pharmaceutical Firms in Nigeria

The study examined the effect of financial distress indicators on the share price of pharmaceutical firms in Nigeria. Altman Zeta Score, operating cash flow, and debt-equity ratio were the financial distress indicators used for the study, while the share price was the dependent variable of the study. The study adopted an ex-post-facto research design, covering the period between 2009 and 2018. Secondary data were extracted from the annual reports and accounts of the sampled pharmaceutical firms in Nigeria. Simple fixed-effect regression analysis was used for the panel data analysis. In line with the specific objectives of the study which is to ascertain the effect of Altman Zeta Score, operating cash flow, and debt-equity ratio on the share price of pharmaceutical firms in Nigeria, it was revealed that Altman Zeta Score has a positive and insignificant effect on share price while operating cash flow has a positive and significant effect on the share price. However, the debt-equity ratio has a negative and insignificant effect on the share price of pharmaceutical firms in Nigeria. The study, therefore, recommended that distressed pharmaceutical firms according to the Zeta Score model should improve their management and efficiency of their employees. This is because the failures of these firms are partly caused by poor management of both resources and staff. Means of generating extra cash from operating activities should be vigorously pursued so as to increase the cash these firms generate from the issue of shares, which will help them come out of distress zone. They should reduce the rate at which they use debt to finance their activities. According to Modgliani and Miller (1963), there is a certain point at which further use of debt becomes unfavourable and continuous use of debt will increase both the agency cost and bankruptcy cost which has the implication of reducing the value of the firm leading to the likelihood of financial distress.

Should Firms Stay 'Private' or Should Firms Go 'Public'? The Impact of IPO on Firm Risk

Using a unique dataset consisting of firms that went public on the European and Asian Stock Exchanges between 2007 and 2011, firms that remain private over the same period and companies which have been listed for at least 10 years, we investigate whether going public is riskier than remaining private. To achieve this goal, we disentangle the effect of equity issue from other IPO’s effect and control for endogeneity and survivorship bias. Our main results are as follows. First, we find that while controlling for selection bias and the effect of equity issue, the risk of financial distress of IPOs starts to increase significantly more than control privately held firms after the listing. This result is resilient to different estimation models (namely treatment effect model, IV approach and DID) and financial distress indicators and to splitting the sample into European and Asian IPOs subsamples. Second, we find that a firm’s risk increases progressively after the IPO year because of a remarkable decline in its liquidity, profitability and retaining earnings and due to a constant increase of its leverage. Third, we find that going public firms also exhibit in the post-IPO years higher risk and lower risk-adjusted performance than the sample of 10-years listed firms. We conclude that the increase of risk by IPO firms is temporary and not related to the public company status.

A qualitative study on cancer patientś experiences with financial burden and financial distress

Abstract Background Financial toxicity was hardly examined in the context of public health. It is proven that financial distress following a cancer diagnosis can have an impact on the quality of life and mortality. Additionally, it was found that subjective indicators of financial toxicity have a stronger effect than objective indicators. Nevertheless, less is known about how higher costs can impact on the individual patient’s well-being. The aim of this study was to analyse the major drivers that lead from financial consequences to subjective financial distress in a country with statutory health insurance. Methods Qualitative semi-structured interviews were conducted with 39 cancer patients, aged between 40 and 86 years, in Germany. Inductive content analysis of data was performed and the individual patient's pathways are recently compared and contrasted. Results Above all, we found that financial distress is not only induced by higher costs and lower available money. Moreover, independently of whether patients experienced any financial decline, they experienced making financial adjustments and feeling financially stressed. The preliminary results show that the patient's ability of good money management and trust in one’s own skills being able to get along with less money might predict psychosocial consequences. Conclusions Screening instruments for financial toxicity are important to effectively detect patients whose quality of life might be worsened by their financial situation. It might be that rather financial skills than the amount of costs are important indicators of financial distress. Key messages Even cancer patients experiencing almost no financial decline during the period of cancer treatment might experience lower quality of life caused by financial distress. The ability and trust in oneself money management might have the strongest impact on subjective financial stress.

Impact of determinants of the financial distress on financial sustainability of Ethiopian commercial banks

The study aims to investigate the impact of determinants of financial distress on financial sustainability of Ethiopian commercial banks. The balanced panel data of 12 commercial banks of Ethiopia have been taken for the study from 2011 to 2017. The research deploys Ordinary Least Square (OLS) Regression Model. The indicators of financial distress are bank’s specific internals and macro-economic factors. The proxies of financial sustainability are Return on Assets, Return on Equity, Financial Stability Index and Bank Soundness. The findings reveal that the Absolute Liquidity Risk and Net Income Growth are found to be positive and significant and Solvency Risk negative and significant in relation to Return on Assets. Asset Quality is found to be positive and significant and Solvency Risk negative and significant with respect to Return on Equity. The Asset Quality and Net Income Risk are positive and significant and Solvency Risk is negative and significant with relation to the Financial Stability Index. Absolute Liquidity Risk and Liquidity Risk are positive and significant and Credit Risk negative and significant with Bank Soundness. Free Cash Flow and Net Income Growth are essential for enhancing Return on Assets and Bank Soundness, and managing equity within the prudential norms could bring forth short-term financial sustainability of commercial banks. By lowering provisioning of loan loss, Growth in Net Interest Income and managing Solvency Risk could ensure financial stability to the banks, which in turn leads to financial sustainability. The study reveals that financial sustainability of banks is insulated from the exposures of systematic risks originating from macroeconomic factors.

Assessing the Determinants of Business Failure of Companies Listed on the Ghana Stock Exchange

This study aims at assessing the determinants of business failure of companies listed on Ghana Stock Exchange using financial ratios as indicators of failure. Using 15 corporate determinants, a collective sample of 25 companies were split into 30% hold out sample, 70% estimation sample and the overall prediction for a cumulative five-year data set. To obtain the significant ratios that bring about business failure, factor Analysis and logit model were respectively employed to reduce the number of correlated variables into smaller uncorrelated variables and to predict the accuracy of the ratios that are significant indicators of failure. From the analysis, the corporate determinants that are consistent indicator of financial distress are profitability ratio, specifically the Return on total asset and Leverage ratio. The study therefore recommends that the regulatory authorities such as the Ghana Stock Exchange and the Securities and Exchange Commission should monitor and assess the financial health of listed firms based on the two significant financial variables (profitability ratio and Leverage ratio).

Bulls and Bears and Bankruptcy- An Early Warning of Distress

This study examines possible indicators of financial distress: financial ratio; financial decision; the preferences of investors; and economic macro conditions. Based on these indicators, the model of financial distress was constructed using capital structure theory. The population in this study is manufacturing companies listed on The Indonesian Stock Exchange from 2003 to 2016. This study relies on the composite market index to detect whether the market is bullish or bearish using regression analysis time series. Then, the factor analysis and logistic regression are used. Models which predict financial distress in bearish markets are more accurate than in a bullish market. Investors, therefore, are more vulnerable ina bullish market. Equity financing will reduce the probability of financial distress in both bullish and bearish markets. This supports the pecking order theory in capital structure - when the companies need funding, an early funding alternative is to retain earnings.

Investigating the Relationship Between Medical Crowdfunding and Personal Bankruptcy in the United States: Evidence of a Digital Divide

As of 2007, an estimated 62% of individual bankruptcy filings in the United States were a direct result of costs borne from medical treatment following illness or injury, up from 46% in 2001. This pressing issue is only getting worse and is in need of relief. In this work, we consider the potential of a relatively recent, and rapidly growing, phenomenon to mitigate the problem: online crowdfunding for medical expenses, wherein patients reach out to their social network for monetary support via online platforms that facilitate the process. On the surface, medical crowdfunding holds the potential to address insurance gaps and to help those burdened by medical debt. However, recent questions have arisen in the healthcare literature around fairness and equity in the distribution of funds. Consistent with the notion of digital divide, many have raised concerns that the individuals most likely to benefit from these services are not the individuals who are most in need. Accordingly, we first seek to establish the effect of this novel phenomenon on a key indicator of financial distress: rates of personal bankruptcy. We then explore heterogeneity in patterns of funding solicitation and acquisition, to assess the presence inequalities across patient populations. We leverage proprietary data from a large medical crowdfunding platform based in the United States, which we combine with county records of personal bankruptcy filings. We report evidence that greater success amongst medical crowdfunding campaigns does translate into a reduction in personal bankruptcy filings. Subsequently, we report analyses which revealed evidence consistent with the presence of a digital divide. Specifically, we report evidence that disadvantaged groups are systematically more likely to launch medical crowdfunding campaigns, yet conditional on campaign launch, garner systematically less in funding. We discuss the implications for the literature on the digital divide, as well as implications for practice and policy.

Bulls and Bears and Bankruptcy- An Early Warning of Distress.

This study examines possible indicators of financial distress: financial ratio; financial decision; the preferences of investors; and economic macro conditions. Based on these indicators, the model of financial distress was constructed using capital structure theory. The population in this study is manufacturing companies listed on The Indonesian Stock Exchange from 2003 to 2016. This study relies on the composite market index to detect whether the market is bullish or bearish using regression analysis time series. Then, the factor analysis and logistic regression are used. Models which predict financial distress in bearish markets are more accurate than in a bullish market. Investors, therefore, are more vulnerable ina bullish market. Equity financing will reduce the probability of financial distress in both bullish and bearish markets. This supports the pecking order theory in capital structure - when the companies need funding, an early funding alternative is to retain earnings.

The Effect of Financial Performance and Financial Distress Indicators to the Stock Price of Bank Rakyat Indonesia

The bank’s financial report is the only lead for the public c to review, evaluate, and assess the soundness of a bank. By tinkering the available figures within the monthly financial reports, we have measured 52 variables comprised of the common indicators to calculate the effects of financial performance of the bank, its financial distress, to its stock price in the market. The common indicators used are the ratios of liquidity, rentability, and solvability. The bankruptcy prediction and financial distress indicators were considered to part ofthe solvability ratios. The data observed and collected was between January 2002 to 18 July 2017. The time lag and IPO as of 10 November 2003 reduced the eligibility of monthly financial reports, leaving the data usable for the period of November 2003 to April 2017. As 10 variables were excluded by the system, only 4 of42 variables were found to be significantly affecting the stock price variable. The 4 independent variables are market capitalization, the ratio of placement in BI to the third-party fund, debt to equity ratio, and debtto asset ratio.

Predicting Bankruptcy via Cross-Sectional Earnings Forecasts

We develop a model to predict bankruptcies, exploiting that negative book equity is a strong indicator of financial distress. Accordingly, our key predictor of bankruptcy is the probability that future losses will deplete a firm’s book equity. To calculate this probability, we use earnings forecasts and their standard deviations obtained from cross-sectional regression models in the spirit of Hou, van Dijk, and Zhang (2012). We add variables that we find to discriminate between bankrupt and non-bankrupt firms. As our model requires only accounting data, we can provide bankruptcy predictions for a wide range of firms, including firms that have no access to capital markets. In strictly out-of-sample tests, we show that our accounting model performs better than alternative corporate failure models that use only accounting information. If we additionally allow for stock market information, our approach also outperforms leading alternatives that require market data.

The effects of ownership structure on likelihood of financial distress: an empirical evidence

PurposeThe purpose of this paper is to explore the role of corporate governance proxies by ownership structure on the likelihood of firms’ financial distress for a sample of 146 Pakistani public-limited companies listed at the Karachi Stock Exchange over the period of 2003-2012.Design/methodology/approachThe dynamic generalized method of moments (GMM) estimator and panel logistic regression (PLR) are used to determine the impact of corporate governance on the financial distress. The ownership structure is used as a determinant of corporate governance, while the Altman Z-score is utilized as an indicator of financial distress, as it measures financial distress inversely. The smaller the values of the Z-score, the higher will be the risk of financial distress.FindingsThe authors find insignificant impact of ownership structure on firms’ likelihood of financial distress based on the dynamic GMM method. However, the PLR results indicate that foreign shareholdings have a significant negative association with firms’ likelihood of financial distress, in the case of Pakistan. An evidence of a negative and insignificant relationship between institutional ownership and financial distress was observed, which indicates the passive role of institutional investors in Pakistan. The results also reveal a positive and significant relationship between insider’s ownership and likelihood of financial distress. This finding is consistent with the entrenchment hypothesis which predicts that insiders are more aligned with their self-interest than outside shareholders’ interest when their shareholding increases in the business. Furthermore, the results also reveal insignificant association between government shareholdings and the probability of financial distress. The reason could be the social welfare objective of the government entities rather than profit maximization.Practical implicationsThe findings of this study provide more insight to corporate managers and investors about the association between the quality of corporate governance and the degree of financial distress, with respect to Pakistani firms. Furthermore, this study contributes to the existing literature by adding new evidence from developing countries like Pakistan which are helpful for regulatory bodies and policymakers in the formulation of long-term corporate governance strategies to manage the financial distress. It is well established that strengthening the quality of corporate governance practices enhances the efficiency of capital markets and reduces the probability of financial distress.Originality/valueThe study extends the body of existing literature on corporate governance and the likelihood of financial distress with reference to Pakistan. The results suggest that policymakers may pay special attention to the quality of corporate governance, specifically ownership structure, while predicting corporate financial distress.

Use of Altman’s Z score and Merton Model by Banks to Predict Bankruptcy in Indian Corporates

There has been a recent increase in the financial distress in assets of the banking industry. Constant defaults by corporate houses have led banks reach gross NPA levels of 5%.One major reason for this rise can be improper risk assessment by banks while giving out loans and improper monitoring of their portfolio companies. And further Indian banks do not use the most robust risk assessment tools and fail in taking early warning action. The paper tries to use two popular models, namely the Altman Zscore model and the Merton Model to predict financial distress in companies which have been the top defaulters in the recent past.The paper tried to determine whether such models are effective in predicting financial distress and how much before the occurrence of the actual event. Financial ratios and other quantitative data from March 2009- March 2013 forms the sample for the study for Kingfisher Airlines, MoserBaer, Gammon India, Educomp Solutions and Deccan Chronicles. The study found Merton model to be a better indicator of financial distress (of companies) than Altman Z score model. However, none of the models were able to judge the possibility of default at the time of issuance of loan indicating at its limitation. Nevertheless, these models which essentially are data driven for assessing the credit risk must widely be used by banks more often, replacing the existing reliance on simple ratios and intuition method.

Indicators of financial distress - An empirical study of Indian Textile sector

 AbstractBusinesses across the globe faces challenges to ensure stability, growth and sustainability. Companies have to deal with changes in economic, social, cultural, political and technological environment. Companies failing to do may face financial distress causing default in payment of contractual obligations and erosion of shareholders wealth. In a business scenario where the stakeholders are many viz. shareholders, lenders, employees, government and society at large, protection of the interests of the stakeholders assume prime importance. Company’s management are expected to identify signals that indicate distress and take remedial measures. This paper attempts to identify distress signals in textile sector in India. Textile sector is one of the largest sector in India. However one third of companies in this sector have reported losses for the previous year. This study aims to examine the factors that can differentiate a distressed company from a non- distressed company so that the factors signifying distress can be studied. Listed companies in textile sector incurring continuous losses for three years were selected for the study. Financial ratios were used as variables. Logistic regression was applied to identify the most important factors indicating distress. It was observed that ratios measuring profitability and efficiency were significant in predicting distress. Key words:  Financial distress, distress signals, textile sector, continuous losses, financial ratios

Predictability of sustainable investments and the role of uncertainty: evidence from a non-parametric causality-in-quantiles test

ABSTRACTIn this article, we examine sustainable investments returns predictability based on the U.S. Dow Jones Sustainability Index (DJSI) and a wide set of uncertainty and financial distress indicators for the period 2002:01–2014:12. To this end, we employ a novel non-parametric causality-in-quantile approach that captures non-linearities in returns distribution. Based on our findings we conclude that the aggregate economic policy uncertainty (EPU) indicator and some components have predictive ability for real returns of the U.S. sustainable investments index. Moreover, if we split our sample to before and after the global financial crisis our results suggest that predictors carry causal information for real returns only in the after-crisis period. Finally, some marginal evidence of predictability from sovereign debt is also observed at the lower and upper ends of the conditional distribution of the real returns of sustainable investments. Our results might entail policy implications for investors and market authorities.

SME recovery following a financial crisis: Does debt overhang matter?

The years before the financial crisis saw a dramatic build-up in private debt levels in several countries and this increase was particularly marked in Ireland. In this paper, we look at whether outstanding debt taken out by small and medium sized enterprises in Ireland constrains current performance following the financial crisis. We find that higher debt burdens (measured as the ratio of debt-to-turnover) have significant negative effects on all measures of firm performance, in particular investment, employment and indicators of financial distress. We find the effects are greatest for sectors and enterprises most reliant on domestic demand which collapsed following the crisis. The effects are also strongest for enterprises that were in the mid-lifecycle, gearing phase, prior to the crisis.

Precision of the models of Altman, Springate, Zmijewski, and Grover for predicting the financial distress

Financial distress models need to be developed as a model of an early warning system. Such an effort is intended to anticipate the conditions that can lead to the bankruptcy of the company. This study aims to analyze the accuracy of the model of Altman, Springate, Zmijewski, and Grover as the best predictor of financial distress. This research is a quantitative study in which the data were collected by means of a data pool. This is done by using a dummy variable. The sample consists of 132 companies which are listed on the list of Daftar Efek Syariah (DES) in 2009-2012. The analysis isdone by using an analytical tool that is a Binary Logistic Regression. It shows that the model of Altman, Zmijewski models, Springate, and Grover can be used for prediction of financial distress. However, the model of Zmijewski is the most appropriate model to be used for predicting the financial distress because it has the highest level of significance compared to the other models. Zmijewski model is used for having more emphasis on the leverage ratio as an indicator of financial distress.

Break-even maturity as a guide to financial distress

During the recent crisis, lags in the transmission mechanism of economic shocks, together with monetary and fiscal policy, made it difficult to assess the evolving dynamics of creditworthiness. As such, developments in financial markets became a key guide for investors and policymakers in determining the degree of financial distress that borrowers faced, providing a real-time update of market participants’ views. However, simple measures of borrowing costs such as secondary market yields typically ignore differences in debt maturities and hence refinancing risks. This paper describes a new indicator of financial distress – the break-even maturity – that combines these factors. Using financial market data for euro area countries, the break-even maturity is shown to provide an alternative perspective on the absolute and relative risks associated with different borrowers that is distinct from the standard metrics gleaned from bond yields or credit-default swaps. As such, while break-even maturities are ultimately theoretical constructs, they can offer a valuable alternative perspective on how the financing pressures facing distressed borrowers are evolving in real-time.

The financial distress indicators trend in Italy: an analysis of medium-size enterprises

This study analyses financial distress as evidenced by financial ratios calculated for Italian medium-sized enterprises from 1989 to 2007, the study is carried out by means of a Dynamic Factorial Analysis (DFA). The data for the Italian firms come from about 240,000 surveys’ records and financial statements over the period. Four basic areas identified as being economically significant in affecting the financial distress include: the leverage index, the measure of the efficiency, the measure of performance, and the measure of liquidity. The financial distress trend has been analysed through a “synthetic” indicator summarizing the information represented by financial ratios by means of a dynamic factorial analysis. The results highlight a slight increase in financial distress over the period and different behaviours of the financial distress indicator among the Italian industries. In particular specific tendencies are detected for capital intensive sectors and for export sectors.

INSOLVENCY PREDICTION IN THE PRESENCE OF DATA INCONSISTENCIES

SUMMARYIn this paper we use data inconsistencies as an indicator of financial distress. Traditional models for insolvency prediction normally ignore inconsistent data, either by removing or replacing it. Instead of removing that information, we propose a new variable to capture it; using it together with traditional accounting variables (based on financial ratios) for the purpose of insolvency prediction.Computational tests use three datasets based on the financial results of 2033 Brazilian Health Maintenance Organizations over 7 years (2001 to 2007). Sixteen classification methods were used to evaluate whether or not the new variable impacted solvency prediction. Tests show a statistically significant improvement in classification accuracy – average results improve 1.3 (p = 0.003) and 1.8 (p = 0.006) percentage points, for 10‐fold and leave‐one‐out cross‐validations respectively. In addition, the analysis of false positives and false negatives shows that the new variable reduces the potentially harmful misclassification of false negatives (i.e. financially distressed companies being classified as financially healthy) and also reduces the estimated overall error rate.Regarding the extensibility of the results, even though this work uses data from Brazilian companies only, the calculation of the financial ratios variables, as well as the inconsistencies, could be extended to most companies worldwide subject to governmental accounting regulations aligned with the International Financial Reporting Standards. Copyright © 2014 John Wiley & Sons, Ltd.