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Gottardo, Pietro, and Anna Maria Moisello. "Family firms, risk-taking and financial distress." Problems and Perspectives in Management 15, no. 2 (June 30, 2017): 168–77. http://dx.doi.org/10.21511/ppm.15(2-1).2017.01.
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The authors investigate the question of whet her qualitative characteristics are likely to explain the survival of family firms in case of financial distress and whether these variables improve the explanatory power of quantitative variables in clarifying the different probability of distress between family and non-family firms. They focus their attention on the impact of the controlling owner and, using the Socioemotional Wealth theory (SEW), study the role of the family involvement in mitigating or accentuating the likelihood of distress. Using a dataset of 1,137 Italian family and non-family firms during 2004–2013, the authors found that family firms are significantly less likely to incur distress than non-family firms. The board dimension and the number of family members on board affect the probability of distress even controlling for some firm risk characteristics such as beta and ROA volatility, and there is also evidence of a gender mitigating effect in case of a female CEO.
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Kozlowski, Steven E., and Michael R. Puleo. "Financial distress, corporate takeovers and the distress anomaly." Managerial Finance 47, no. 8 (March 30, 2021): 1168–93. http://dx.doi.org/10.1108/mf-12-2019-0621.
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PurposeThis 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.Design/methodology/approachThe 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.FindingsDistressed 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.Originality/valueThe 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.
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Meher, Kishor, and Henok Getaneh. "Impact of determinants of the financial distress on financial sustainability of Ethiopian commercial banks." Banks and Bank Systems 14, no. 3 (October 10, 2019): 187–201. http://dx.doi.org/10.21511/bbs.14(3).2019.16.
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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.
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Wang, Qian. "Financial Distress Risk and Momentum Effects: Evidence from China’s Stock Market." International Journal of Economics and Finance 9, no. 12 (November 13, 2017): 153. http://dx.doi.org/10.5539/ijef.v9n12p153.
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I examine the relation of distress risk to size, book-to-market, and momentum effects in China’s stock market. Consistent with the market underreaction hypothesis, I find that distressed firms underperform non-distressed firms in China’s stock market and the momentum factor proxies for distress risk in our sample period. My study also shows that the explanatory power of the momentum effect is subsumed when the distress factor is present.
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Chalise, Lekhnath, and Sophia Anong. "Spending Behavior Change and Financial Distress During the Great Recession." Journal of Financial Counseling and Planning 28, no. 1 (2017): 49–61. http://dx.doi.org/10.1891/1052-3073.28.1.49.
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This study investigated whether spending habits before and during the Great Recession predicted financial distress. Financial distress was defined as failing to make mortgage and non-mortgage loan payments on time. Data from the 2007–2009 panel of the Survey of Consumer Finances revealed that one’s prerecession spending habit did not seem to matter. Respondents who reported in the earlier wave that they spent more than income but had begun to spend less than income during the recession were twice as likely to become financially distressed. However, those who were spending more than their income during the recession were three times as likely to be financially distressed. Being in good health, having income certainty, and above average risk tolerance lowered the odds of financial distress.
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Simlai, Prodosh. "Firm characteristics, distress risk and average stock returns." Accounting Research Journal 27, no. 2 (August 26, 2014): 101–23. http://dx.doi.org/10.1108/arj-06-2012-0046.
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Purpose – 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. Design/methodology/approach – 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. Findings – 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. Research limitations/implications – 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. Practical implications – 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. Originality/value – 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.
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Bartram, Söhnke M., Gregory W. Brown, and William Waller. "How Important Is Financial Risk?" Journal of Financial and Quantitative Analysis 50, no. 4 (August 2015): 801–24. http://dx.doi.org/10.1017/s0022109015000216.
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AbstractWe explore the determinants of equity price risk of nonfinancial corporations. Operating and asset characteristics are by far the most important determinants of risk. For the median firm, financial risk accounts for only 15% of observed stock price volatility. Furthermore, financial risk has declined over the last 3 decades, indicating that any upward trend in equity volatility was driven entirely by economic risk factors. This explains why financial distress (as opposed to economic distress) was surprisingly uncommon in the nonfinancial sector during the 2007–2009 crisis even as measures of equity volatility reached unprecedented highs.
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Chang, Woo-Jin, Rachel M. Hayes, and Stephen A. Hillegeist. "Financial Distress Risk and New CEO Compensation." Management Science 62, no. 2 (February 2016): 479–501. http://dx.doi.org/10.1287/mnsc.2014.2146.
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ALMEIDA, HEITOR, and THOMAS PHILIPPON. "The Risk-Adjusted Cost of Financial Distress." Journal of Finance 62, no. 6 (November 28, 2007): 2557–86. http://dx.doi.org/10.1111/j.1540-6261.2007.01286.x.
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Almeida, Heitor, and Thomas Philippon. "Estimating Risk-Adjusted Costs of Financial Distress." Journal of Applied Corporate Finance 20, no. 4 (September 2008): 105–9. http://dx.doi.org/10.1111/j.1745-6622.2008.00208.x.
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Andreou, Christoforos K., Panayiotis C. Andreou, and Neophytos Lambertides. "Financial distress risk and stock price crashes." Journal of Corporate Finance 67 (April 2021): 101870. http://dx.doi.org/10.1016/j.jcorpfin.2020.101870.
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Eisdorfer, Assaf, and Efdal Ulas Misirli. "Distressed Stocks in Distressed Times." Management Science 66, no. 6 (June 2020): 2452–73. http://dx.doi.org/10.1287/mnsc.2019.3314.
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We partially explain the well-documented distress anomaly by studying the risk/return relation of distressed stocks across market states. We show that the anomaly does not hold in market downturns. The asset beta and financial leverage of distressed stocks rise significantly during bear markets, resulting in a dramatic increase in their equity beta. Hence, a long/short healthy-minus-distressed trading strategy leads to significant losses when the market rebounds. Managing this risk mitigates the severe losses of financial distress strategies and significantly improves their Sharpe ratios. Our results remain strongly significant controlling for the momentum effect and are robust to various estimation procedures. This paper was accepted by Tyler Shumway, finance.
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Lord, Justin, Amy Landry, Grant T. Savage, and Robert Weech-Maldonado. "Predicting Nursing Home Financial Distress Using the Altman Z-Score." INQUIRY: The Journal of Health Care Organization, Provision, and Financing 57 (January 2020): 004695802093494. http://dx.doi.org/10.1177/0046958020934946.
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This article uses a modified Altman Z-score to predict financial distress within the nursing home industry. The modified Altman Z-score model uses multiple discriminant analysis (MDA) to examine multiple financial ratios simultaneously to assess a firm’s financial distress. This study utilized data from Medicare Cost Reports, LTCFocus, and the Area Resource File. Our sample consisted of 167 268 nursing home-year observations, or an average of 10 454 facilities per year, in the United States from 2000 through 2015. The independent financial variables, liquidity, profitability, efficiency, and net worth were entered stepwise into the MDA model. All of the financial variables, with the exception of net worth, significantly contributed to the discriminating power of the model. K-means clustering was used to classify the latent variable into 3 categorical groups: distressed, risk-of-financial distress, and healthy. These findings will provide policy makers and practitioners another tool to identify nursing homes that are at risk of financial distress.
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Kristanti, Farida Titik, and Aldrin Herwany. "Corporate Governance, Financial Ratios, Political Risk and Financial Distress: A Survival Analysis." Accounting and Finance Review (AFR) Vol.2(2) Apr-Jun 2017 2, no. 2 (March 16, 2017): 26–34. http://dx.doi.org/10.35609/afr.2017.2.2(4).
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Objective - The objective of this study was to investigate the factors like corporate governance, financial ratios, and political risk and their impacts on company's survival. Methodology/Technique - Collecting data of Indonesian Stock Exchange from 2000 to 2014 and employing purposive random sampling, this research collects samples of 58 companies undergoing financial distress and 275 others which do not. Findings - The research eventually proves that agency theory and Asymmetric Information theory do occur in Indonesia. With Cox Proportional Hazard model, it then proves that all two models employed: independence commissioners, leverage, operating risk, size, return on asset and control of corruption, are variables which consistently affect financial distress of the company. Novelty - The study uses original data and gives supported suggestion for the researched issues. Type of Paper: Empirical Keywords: Financial Distress; Financial Ratios; Corporate Governance; Political Risk. JEL Classification: G01,G34, M48
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Boyer, M. Martin, and Monica Marin. "Financial Distress Risk and the Hedging of Foreign Currency Exposure." Quarterly Journal of Finance 03, no. 01 (March 2013): 1350002. http://dx.doi.org/10.1142/s201013921350002x.
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We examine the use of foreign currency hedging instruments by US manufacturing firms during 1996–2004, and assess their impact on the firms' risk of financial distress. We derive measures of financial distress using the Black–Scholes–Merton option pricing model and find that the use of foreign currency hedging instruments reduces the firms' financial distress. The main findings are confirmed when examining alternate measures of foreign currency exposure, econometric specifications or measures of financial distress.
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El-ansari, Osama, and Lina Bassam. "Predicting Financial Distress for Listed MENA Firms." International Journal of Accounting and Financial Reporting 9, no. 2 (April 15, 2019): 51. http://dx.doi.org/10.5296/ijafr.v9i2.14542.
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Financial distress prediction gives an early warning about defaulting risk for firms; thus, it is a real concern of the entire economy.Purpose: To examine the determinants of financial distress across MENA region countries, by using definitions of distress and historical data from active listed firms in the region.Methodology: logistic regression is run on firm-specific variables and a set of macroeconomic variables to develop a prediction model to examine the effect of these predictors on the probability of financial distress.Findings: it has been found that after controlling for country effects, accounting ratios, firm size, and macroeconomic variables provided an acceptable prediction model for listed MENA firms.Originality: a gap exists in the literature of developing countries’ prediction for financial distress. Many studies addressed bankruptcy prediction for a certain country in the region, however, a limited number of researches approached predicting distressed models for listed firms in the region.
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Gul, Ferdinand A., Mehdi Khedmati, Edwin KiaYang Lim, and Farshid Navissi. "Managerial Ability, Financial Distress, and Audit Fees." Accounting Horizons 32, no. 1 (September 1, 2017): 29–51. http://dx.doi.org/10.2308/acch-51888.
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SYNOPSIS This study examines whether the relationship between managerial ability and audit fees is conditional on financial distress. We find that higher managerial ability increases audit fees in financially distressed firms and decreases audit fees in non-distressed firms. We also observe that financially distressed firms with higher-ability managers display lower accrual quality and a higher likelihood of restatement. Moreover, higher-ability managers in distressed firms engage more in opportunistic financial reporting to concurrently maximize equity-based compensation and cope with debt refinancing pressures, which increases audit risks and results in greater audit fees. We confirm our results using a battery of sensitivity and additional analyses.
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Hanafi, Ahmad Harith Ashrofie, Rohani Md-Rus, and Kamarun Nisham Taufil Mohd. "PREDICTING FINANCIAL DISTRESS IN MALAYSIA AND ITS EFFECT ON STOCK RETURNS." Vol. 16, Number 2, 2021 16, Number 2 (June 15, 2021): 81–110. http://dx.doi.org/10.32890/ijbf2021.16.2.4.
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Unstable economic conditions have an adverse impact on the financial performance of firms, leading to financial distress, which is an unfavourable situation for investors as it may affect their investment returns. Thus, this study attempted to predict financial distress and to examine the effect of financial distress on stock returns by using firms listed on Bursa Malaysia from 1990 to 2020. This study used the logit model to find the probability of bankruptcy and also as a proxy for financial distress risk in the asset pricing model. From this study, financial distress risk was found to be insignificant in pricing stock returns in all tested models. This finding demonstrates that financial distress risk does not affect stock returns since this risk may be eliminated through diversification.
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Rahman, Mahfuzur, Cheong Li Sa, and Md Abdul Kaium Masud. "Predicting Firms’ Financial Distress: An Empirical Analysis Using the F-Score Model." Journal of Risk and Financial Management 14, no. 5 (May 1, 2021): 199. http://dx.doi.org/10.3390/jrfm14050199.
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Financial performance of firms is very important to bankers, shareholders, potential investors, and creditors. The inability of firms to meet their liabilities will affect all its stakeholders and will result in negative consequences in the wider economy. The objective of the study is to explore the applicability of a distress prediction model which uses the F-Score and its components to identify firms which are at high risk of going into default. The study incorporates a prediction model and vast literature to address the research questions. The sample of the study is collected from publicly listed firms of the United States. In total, 81 financially distressed firms wereextracted from the UCLA-LoPucki Bankruptcy Research Database during 2009–2017. This study found that the relationship of the F-Score and probability of firms going into financial distress is significant. This study also demonstrated that firms which are at risk of distress tend to record a negative cash flow from operations (CFO) and showed a greater decline in return on assets (ROA) in the year prior to default. This study extends the existing literature by supporting a model which has not been widely used in the area of financial distress predictions.
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LIU, WEIXI, and IAN TONKS. "Alternative risk-based levies in the pension protection fund for multi-employee schemes." Journal of Pension Economics and Finance 8, no. 4 (June 16, 2009): 451–83. http://dx.doi.org/10.1017/s1474747209004016.
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AbstractThis paper estimates the risks of financial distress in UK universities, and uses these estimates to examine the basis of the annual levies paid to the UK's Pension Protection Fund by the Universities Superannuation Scheme, a multi-employer scheme covering 391 universities and related institutions. The paper compares the payments between the two alternative participating arrangements for multi-employer pension schemes to the PPF, namely last-man-standing and segmented levies. Using an Ohlson (1980) logit model to predict the financial distress risk for HE institutions, we find that financially distressed institutions are smaller, with higher leverage and lower earnings. By comparing the implied financial distress probabilities from the PPF risk-based levy using USS accounts with the simulated probabilities using our logit model, we estimate whether USS levies are fairly priced. Our estimates suggest that in 2006/07 USS member institutions appeared to be paying less than the fair risk-based levy. However, this is because during the initial phase of the PPF the risk-based levies were much lower as a proportion of the total levy than the intended steady-state values. The implication is that if USS had paid the same total levy but where the risk-based component was four fifths of the total, then USS would have been paying substantially more than its fair risk-based levy. In addition, by looking at the distributions of individual university risk-based levies under a segmented PPF arrangement, we find evidence of significant cross-subsidies under the current last-man-standing levy between participating USS institutions.
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Peake, Charles F. "Does Financial Distress Risk Drive the Momentum Anomaly?" CFA Digest 39, no. 1 (February 2009): 57–59. http://dx.doi.org/10.2469/dig.v39.n1.28.
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Agarwal, Vineet, and Richard Taffler. "Does Financial Distress Risk Drive the Momentum Anomaly?" Financial Management 37, no. 3 (September 2008): 461–84. http://dx.doi.org/10.1111/j.1755-053x.2008.00021.x.
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Boubaker, Sabri, Alexis Cellier, Riadh Manita, and Asif Saeed. "Does corporate social responsibility reduce financial distress risk?" Economic Modelling 91 (September 2020): 835–51. http://dx.doi.org/10.1016/j.econmod.2020.05.012.
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Wijayanti, Kristina Nimas, Inayah Adi Sari, and Dewi Indriasih. "Pengaruh Risk Profile, Good Corporate Governance, Earnings, dan Capital Terhadap Prediksi Financial Distress Pada Bank Perkreditan Rakyat." Permana : Jurnal Perpajakan, Manajemen, dan Akuntansi 10, no. 1 (February 28, 2018): 87–106. http://dx.doi.org/10.24905/permana.v10i1.69.
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This study aims to determine the effect of Risk Based Bank Rating on the prediction of financial distress in Rural Banks in the area of ex Residency of Pekalongan with the period of research in 2013 until 2017. This study of financial distress uses a quantitative approach towards all BPR in Indonesia by using purposive sampling method. Data analysis method used is logistic regression analysis with the dependent variable in the form of dummy variables, namely 1 for non-financial distress and 2 for financial distress. Determination of the financial distress category was determined based on the Financial Services Authority Regulation No.5 / POJK.03 / 2015, that BPR with core capital below Rp6 billion indicated experiencing financial difficulties and vice versa. The results of the research showed that (1) Risk Profile represented by the LDR and NPL ratios had a positive and insignificant effect on financial distress. (2) Good Corporate Governance (GCG) represented by the composite value of the self-assessment report on the application of BPR governance has a positive effect but not significant to financial distress. (3) Earnings represented by the ROA ratio have a positive and insignificant effect on financial distress. (4) Capital represented by the CAR ratio has a negative effect and is not significant to financial distress.
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Trussel, John M., and Patricia A. Patrick. "Assessing and ranking the financial risk of municipal governments." Journal of Applied Accounting Research 19, no. 1 (February 12, 2018): 81–101. http://dx.doi.org/10.1108/jaar-05-2016-0051.
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Purpose The purpose of this paper is to develop a model to assess and rank the financial risk of a municipal government (“municipality”). Financial risk is the likelihood that a municipality will experience financial distress. Design/methodology/approach Logistic regression is used with financial indicators to assess the level of financial risk. Then, the municipalities are ranked according to their financial risk. As predictor variables for the regression model, indicators are used that were developed by a Pennsylvania state agency to monitor the financial condition of municipalities. Findings Financial risk is positively associated with debt service, population, tax effort, and public service on roadways, while negatively correlated with intergovernmental revenues, operating position, user charges, capital outlays, fund balances, and tax revenue concentration. The financial risk model is able to correctly classify up to 99 percent of municipalities as either at risk or not at risk of financial distress. Research limitations/implications The financial risk model was developed using data from one state in the USA. Further research is needed to test the model’s application to other states and countries. Practical implications Financial risk is on the rise since the Great Recession. This study may be used by municipal managers, citizens, creditors, and regulators to assess and rank the financial risk of a municipality. Originality/value This study provides a method of classifying municipalities as either at risk or not at risk of financial distress. Previous models of the financial condition of municipalities do not provide a method of assessing and ranking financial risk.
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Lin, Hsuan-Chu, Shao-Huai Liang, She-Chih Chiu, and Chieh-Yuan Chen. "Leverage and employee compensation – the perspective of human capital." International Journal of Managerial Finance 15, no. 1 (February 4, 2019): 62–78. http://dx.doi.org/10.1108/ijmf-11-2017-0247.
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Purpose The purpose of this paper is to empirically test the predictions in Titman (1984) and Berk et al. (2010) which indicate that firms with higher leverage will pay chief executive officer (CEO) and employee more. In addition, this paper examines whether financial distressed firms utilize leverage as a bargaining tool to reduce labor costs. Design/methodology/approach This paper conducts ordinary least squares regression analysis to investigate: CEO compensation which represents critical employees and lower-level employee compensation which represents less critical employees. Empirical data consist of US publicly held companies during the period between 2006 and 2013. Findings This paper finds that firms with higher levels of leverage tend to compensate employees for their human capital risk and that financially distressed firms consider leverage a bargaining tool by which to depress labor costs, which leads to lower employee compensation as compared to that of financially healthy firms. Research limitations/implications This paper highlights the importance of keeping balance between human capital and labor costs. In the case that human capital risk might not be fully compensated by firms facing financial distress, vicious cycle could occur because a failure of considering human capital might invite unrecoverable consequence. This could be done in future research. Originality/value This paper has three contributions. First, this paper supports the Titman (1984) and Berk et al. (2010) by empirically documenting that high-leveraged firms compensate their employees for potential human capital risk. Second, this paper adds to the literature by empirically providing that human capital risk might not be fully compensated if the firms are facing financial distress. Finally, this paper contributes to the authorities by showing that employees’ interests may be sacrificed if the firm is under financial distress.
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Mukhlis, Ervie Nur Afifa, and Sylviana Maya Damayanti. "Enterprise Risk Management to Minimizing Financial Distress Condition Using Analytical Hierarchy Process Method in PT. XYZ." European Journal of Business and Management Research 6, no. 1 (January 13, 2021): 76–86. http://dx.doi.org/10.24018/ejbmr.2021.6.1.668.
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PT. XYZ as one of telecommunications infrastructure providers that suffered losses gave a strong signal that the company was experiencing financial distress. Altman z-score is used to know the condition of the company. The result of Altman z-score analysis company has to further analyze the cause of financial distress. To prevent the company from bankruptcy risk, we cannot only focus on the financial aspect but also from various aspect. Enterprise risk management is used as a tool to identify what risks that could lead companies to experience financial distress and which risk should be mitigated. Risk assessment in this study using the analytic hierarchy process to check and reduce the expert inconsistency. After conducting risk management process, monitoring and review as the final step and implementation of this study. The result from this study is most of the risk are classified into high and medium risk can be mitigate by reduce or transfer the risk depend on the most suitable risk treatment. There are risks that classified as low risk, environment risk and promotion risk.
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Putri, Elysa Lisitiana. "Prediksi financial distress dengan analisis risk, good corporate governance, earningsc Capital, dan size pada Bank Umum Swasta Nasional Devisa." Management and Business Review 2, no. 2 (December 27, 2018): 93–105. http://dx.doi.org/10.21067/mbr.v2i2.3226.
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The research aims to predict financial distress at the Foreign Exchange National Private Commercial Bank by using analysis of risk, good corporate governance, earnings, capital and size. Using sample 17 national foreign exchange private banks, and data analysis techniques using Multiple Linear Regression for four conditions, namely all conditions, financial distress conditions, gray area conditions, and non financial distress conditions. The results of this study indicate that the NPL and the proportion of independent commissioners do not have a significant effect on all conditions, financial distress conditions, gray area conditions, and non financial distress conditions. ROA has a significant effect only for all conditions, gray area, and non financial distress conditions. CAR has a significant effect on all conditions, and financial distress conditions, size only has a significant effect on all conditions and conditions in the gray area.
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Asyikin, Jumirin, Grahita Chandrarin, and Harmono. "Effect of Financial Performance against Financial Distress through Risk in Islamic Banks." International Journal of Advances in Scientific Research and Engineering 05, no. 11 (2019): 107–13. http://dx.doi.org/10.31695/ijasre.2019.33592.
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Ho, Kung-Cheng, Shih-Cheng Lee, Po-Hsiang Huang, and Ting-Yu Hsu. "Distress risk and leverage puzzles: Evidence from Taiwan." Risk Governance and Control: Financial Markets and Institutions 6, no. 2 (2016): 72–78. http://dx.doi.org/10.22495/rcgv6i2art9.
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Financial distress has been invoked in the asset pricing literature to explain the anomalous patterns in the cross-section of stock returns. The risk of financial distress can be measured using indexes. George and Hwang (2010) suggest that leverage can explain the distress risk puzzle and that firms with high costs choose low leverage to reduce distress intensities and earn high returns. This study investigates whether this relationship exists in the Taiwan market. When examined separately, distress intensity is found to be negatively related to stock returns, but leverage is found to not be significantly related to stock returns. The results are the same when distress intensity and leverage are examined simultaneously. After assessing the robustness by using O-scores, distress risk puzzle is found to exist in the Taiwan market, but the leverage puzzle is not.
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Yousaf, Umair Bin, Khalil Jebran, and Man Wang. "Can board diversity predict the risk of financial distress?" Corporate Governance: The International Journal of Business in Society 21, no. 4 (January 20, 2021): 663–84. http://dx.doi.org/10.1108/cg-06-2020-0252.
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Purpose The purpose of this study is to explore whether different board diversity attributes (corporate governance aspect) can be used to predict financial distress. This study also aims to identify what type of prediction models are more applicable to capture board diversity along with conventional predictors. Design/methodology/approach This study used Chinese A-listed companies during 2007–2016. Board diversity dimensions of gender, age, education, expertise and independence are categorized into three broad categories; relation-oriented diversity (age and gender), task-oriented diversity (expertise and education) and structural diversity (independence). The data is divided into test and validation sets. Six statistical and machine learning models that included logistic regression, dynamic hazard, K-nearest neighbor, random forest (RF), bagging and boosting were compared on Type I errors, Type II errors, accuracy and area under the curve. Findings The results indicate that board diversity attributes can significantly predict the financial distress of firms. Overall, the machine learning models perform better and the best model in terms of Type I error and accuracy is RF. Practical implications This study not only highlights symptoms but also causes of financial distress, which are deeply rooted in weak corporate governance. The result of the study can be used in future credit risk assessment by incorporating board diversity attributes. The study has implications for academicians, practitioners and nomination committees. Originality/value To the best of the authors’ knowledge, this study is the first to comprehensively investigate how different attributes of diversity can predict financial distress in Chinese firms. Further, this study also explores, which financial distress prediction models can show better predictive power.
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Cohen, Sandra, Antonella Costanzo, and Francesca Manes-Rossi. "Auditors and early signals of financial distress in local governments." Managerial Auditing Journal 32, no. 3 (March 6, 2017): 234–50. http://dx.doi.org/10.1108/maj-05-2016-1371.
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Purpose This study aims to analyze whether and how a set of financial ratios calculated on the basis of financial statement information would allow auditors of Italian local governments (LGs) to get an indication of LGs’ financial distress risk and, hence, to support politicians and managers in promptly detecting financial distress. Design/methodology/approach A model comprising a set of financial indicators that would distinguish distressed from not distressed LGs through a logistic regression approach has been estimated and applied to Italian LGs. The model is built on the basis of information pertaining to 44 distressed and 53 not distressed LGs for up to five years prior to bankruptcy and covers the period 2003-2012. Findings The model reveals that the percentage of personnel expenses over revenues, the turnover ratio of short-term liabilities over current revenues and the reliance on subsidies (calculated as subsidies per capita) are factors discriminating non-distressed LGs from the distressed ones. Practical implications The model could have political and practical implications. The possible use of this model as a complementary tool in auditing activities might be helpful for auditors in detecting financial distress promptly, thus potentially enabling politicians and managers to search for different ways to manage public resources to avoid the detrimental consequences related to the declaration of distress. Originality/value This model, contrary to existing models that use accrual accounting data, is applicable to LGs that adopt a modified cash accounting basis.
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Mall, Sunita, Tushar R. Panigrahi, and Stephina Thomas. "Predicting Financial Solvency of Commercial Borrowers: The Case of Non-Banking Financial Companies." Accounting and Finance Research 8, no. 3 (July 2, 2019): 61. http://dx.doi.org/10.5430/afr.v8n3p61.
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Credit risk can be effectively managed by evaluating and predicting the credit worthiness of a customer or a corporate. Credit scores are calculated to assess the credit worthiness. It helps the financial institutes to know the amount and dimensions of risk involved in different credit transactions. Credit scoring helps the financial institutes to decide whether or not to lend. It also helps in deciding the price of a particular exposure, the appropriate credit facility and different risk tools. This research paper focuses on identifying the triggers of credit default. It also focuses on checking and predicting the financial solvency of the borrowers of non-banking financial companies and assigning the credit worthiness to these companies. The data is collected from a Mumbai based NBFC. The data for the study are extracted from balance sheet and profit &loss statement of these companies. The data includes the financial ratio variables for forty companies. Altman's Z-score is used to find credit worthiness and DuPont technique is used to find the main causes of financial distress. The results of this research highlights that the borrowing companies having a lower return on equity (ROE) are prone to be in distress zone. This research would help the financial institutions to identify the most likely defaulter companies and to segment the clients/companies in safe, grey and distressed zones. The results are robust to sub-samples.
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Jia, Jing. "Does risk management committee gender diversity matter? A financial distress perspective." Managerial Auditing Journal 34, no. 8 (September 2, 2019): 1050–72. http://dx.doi.org/10.1108/maj-05-2018-1874.
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Purpose Using 2010 corporate governance principles and recommendations (CGPR) as a natural setting, the purpose of this paper is to investigate the relationship between risk management committee (RMC) gender diversity and a firm’s likelihood of financial distress. Empirical evidence regarding whether CGPR (2010) enhances RMC gender diversity (RMCGD) is also provided. Design/methodology/approach Data were collected from the annual reports of the top 300 Australian Stock Exchange (ASX) listed companies from 2007 to 2014. To control for potential endogeneity, the association between (RMCGD) and a firm’s likelihood of financial distress was investigated using an instrumental variable approach (panel 2SLS regression). The relationship between CGPR (2010) and RMCGD was explored using panel regression analysis with firm fixed effects. Findings RMCGD was found to be associated with a lower probability of financial distress, suggesting that women are better at monitoring and reducing firms’ excessive risk-taking behaviours, which, in turn, decreases firms’ risk of financial distress. The results also indicate that CGPR (2010) is quite effective in enhancing committee gender diversity. In the additional analysis, the results show that RMCGD moderates the negative relationship between risk and likelihood of financial distress. Importantly, the proportion of women with financial experience on RMCs is more effective in reducing the likelihood of financial distress compared to the proportion of men with financial experience on RMCs. These results highlight the benefits of having a gender diverse RMC. Research limitations/implications The results were based on the top 300 ASX-listed companies; thus, restricting generalisability. In addition, this study only focussed on listed firms, non-listed firms may add additional insights to the literature. Practical implications The results provide new and useful empirical evidence about RMCGD for Australian policymakers. This paper suggests that, in the short-term at least, RMCGD should be encouraged by regulators. Regulators could also recommend that the firms with a non-diverse RMC include women with financial experience on their RMC. Originality/value Given that prior studies have indicated that gender diversity is closely related to risk, this study contributes to the previous literature by investigating RMCGD and its effect on the likelihood of financial distress. It is expected that the role of RMC member would be to protect the firm from ultimate failure (likelihood of financial distress), especially during a financial crisis.
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ANG, Tze Chuan Chewie. "Are Firms with Negative Book Equity in Financial Distress?" Review of Pacific Basin Financial Markets and Policies 18, no. 03 (September 2015): 1550016. http://dx.doi.org/10.1142/s0219091515500162.
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This study examines whether negative book equity (BE) firms are in financial distress by analyzing their operating performance, financial characteristics, distress risk, and survivability when they first report negative BE. Firms with small magnitude of negative BE (SNBE firms) suffer from persistent negative earnings and financial distress, while firms with large magnitude of negative BE (LNBE firms) experience a temporary non-distress related earnings shock. LNBE firms report consecutive years of negative BE, but have lower distress risk and failure rate than both SNBE and control firms. However, all negative BE stocks have abysmal returns subsequent to their first report of negative BE.
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Yunxiao Liu, 김우찬, and 김중혁. "Business Group and Its Effect on Financial Distress Risk." KOREAN JOURNAL OF FINANCIAL MANAGEMENT 33, no. 3 (September 2016): 57–109. http://dx.doi.org/10.22510/kjofm.2016.33.3.003.
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Ligon, James A., and James Malm. "Litigation risk, financial distress, and the use of subsidiaries." Quarterly Review of Economics and Finance 67 (February 2018): 255–72. http://dx.doi.org/10.1016/j.qref.2017.07.008.
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Lally, Martin. "The risk-adjusted costs of financial distress: a comment." Applied Economics Letters 17, no. 16 (October 28, 2010): 1611–13. http://dx.doi.org/10.1080/13504850903085027.
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Purnanandam, Amiyatosh. "Financial distress and corporate risk management: Theory and evidence." Journal of Financial Economics 87, no. 3 (March 2008): 706–39. http://dx.doi.org/10.1016/j.jfineco.2007.04.003.
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Luthfiyanti, Nur Khalizah, and Lely Dahlia. "The Effect of Enterprise Risk Management on Financial Distress." Journal of Accounting Auditing and Business 3, no. 2 (July 27, 2020): 30. http://dx.doi.org/10.24198/jaab.v3i2.25910.
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Lately, the retail industry has been suffering financial performance problem caused by some factors, such as the trade competition with online trading. Companies in the retail industry sector had to handle this risk to minimize further financial performance problem. The aim of this study is to determined the impact of the implementation of enterprise risk management in avoiding financial distress. This study used binary logistic regression for tool analysis. The sample of this study involved 21 retail companies listed on the Indonesia Stock Exchange from 2013 to 2017. The sample has been selected using a purposive random sampling method. Variable control, namely, liquidity, profitability, leverage, and company size, are included. The result of the study indicates that enterprise risk management implementation was found affecting financial distress
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Yang, He, Emma Li, Yi Fang Cai, Jiapei Li, and George X. Yuan. "The extraction of early warning features for predicting financial distress based on XGBoost model and shap framework." International Journal of Financial Engineering 08, no. 03 (June 23, 2021): 2141004. http://dx.doi.org/10.1142/s2424786321410048.
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The purpose of this paper is to establish a framework for the extraction of early warning risk features for the predicting financial distress based on XGBoost model and SHAP. It is well known that the way to construct early warning risk features to predict financial distress of companies is very important, and by comparing with the traditional statistical methods, though the data-driven machine learning for the financial early warning, modelling has a better performance in terms of prediction accuracy, but it also brings the difficulty such as the one the corresponding model may be not explained well. Recently, eXtreme Gradient Boosting (XGBoost), an ensemble learning algorithm based on extreme gradient boosting, has become a hot topic in the area of machine learning research field due to its strong nonlinear information recognition ability and high prediction accuracy in the practice. In this study, the XGBoost algorithm is used to extract early warning features for the predicting financial distress for listed companies, with 76 financial risk features from seven categories of aspects, and 14 non-financial risk features from four categories of aspects, which are collected to establish an early warning system for the predication of financial distress. With applications, we conduct the empirical testing respect to AUC, KS and Kappa, the numerical results show that by comparing with the Logistic model, our method based on XGBoost model established in this paper has much better ability to predict the financial distress risk of listed companies. Moreover, under the framework of SHAP (SHAPley Additive exPlanations), we are able to give a reasonable explanation for important risk features and influencing ways affecting the financial distress visibly. The results given by this paper show that the XGBoost approach to model early warning features for financial distress does not only preform a better prediction accuracy, but also is explainable, which is significant for the identification of early warning to the financial distress risk for listed companies in the practice.
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Younas, Noman, Shahab UdDin, Tahira Awan, and Muhammad Yar Khan. "Corporate governance and financial distress: Asian emerging market perspective." Corporate Governance: The International Journal of Business in Society 21, no. 4 (February 11, 2021): 702–15. http://dx.doi.org/10.1108/cg-04-2020-0119.
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Purpose The purpose of this paper is to examine the impact of corporate governance index (PAKCGI) on firm financial distress for a sample of 152 non-financial firms listed at Pakistan Stock Exchange (PSX) over the period from 2003 to 2017. Design/methodology/approach To examine the impact of PAKCGI on financial distress (Altman Z-Score), random effect model is applied. The PAKCGI is a self-constructed index based on the five important factors of corporate governance practices, i.e. board of directors, audit committees, right of shareholders, disclosures and risk management. The binary coding approach is adopted for the construction of PAKCGI. Altman Z-Score model is used as a proxy for financial distress indicator. The absolute value of Altman Z-score has been taken as financial distress indicator. Findings The outcomes of the study indicate a positive impact of PAKCGI on risk of firms’ financial distress. The positive coefficient of PAKCGI implies that the good corporate practices work as catalyst to reduce risk of financial distress in Pakistan. A significant negative impact of block holders on financial distress suggests that the concentrated block ownership take monopolistic decision to protect their interests. It has also been observed that significant positive impact of institutional ownership on financial distress exists in the Pakistani listed firms. Furthermore, this study also reveals that significant negative association between board size, CEO duality and financial distress indicator. Research limitations/implications The findings may encourage the Pakistani listed companies to follow and implement good corporate governance practices, which would lead to increase the confidence of investors, regulators and stakeholders. Originality/value The current study extends the corporate governance literature by examining the relationship between the corporate governance attributes and the financial distress status of Pakistani listed companies. From the academic perspective, this paper adds to the knowledge concerning the association between corporate governance practices and risk of financial distress in emerging markets.
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Ndicu, Ndua Daniel. "Financial Innovations Risk, Financial Distress and Firms Value: A Critical Review of Literature." European Scientific Journal, ESJ 14, no. 10 (April 30, 2018): 99. http://dx.doi.org/10.19044/esj.2018.v14n10p99.
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Throughout history, society has always sought for ways and means of responding to life challenges and opportunities. Several scholars support the need for innovation for a firm to remain a good performer during its existence, though the level of risks associated with this kind of undertaking has not received the coveted attention. With the use of financial innovations companies can safely utilize current or go for more risky and up to date technologies that can have a drastic and positive impact on their ventures. Additionally, financial innovations have had a tremendous impact in enriching finance and enhancing the economic prosperity of many firms. However, this financial innovation may also be ruinous to the organization if it is overboard. This study thus sought to review the extant theoretical and empirical literature relating to risky financial innovations, financial distress and firm value. Specifically the study was guided by the following objectives: To review extant theoretical literature on the constructs of risky financial innovations, financial distress and firm value; to review past empirical literature on the constructs of risky financial innovations, financial distress and firm value; to identify the emerging theoretical and empirical gaps that form the basis of future research. Additionally, the study sought to propose a theoretical model to respond to the identified gaps. The study has concluded that financial innovation has positive impact on financial performance and firm value, there is direct relationship between financial innovation and financial deepening and financial innovation enhances growth of the firm.
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Shahwan, Tamer Mohamed. "The effects of corporate governance on financial performance and financial distress: evidence from Egypt." Corporate Governance 15, no. 5 (October 5, 2015): 641–62. http://dx.doi.org/10.1108/cg-11-2014-0140.
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Purpose – This paper aims to empirically examine the quality of corporate governance (CG) practices in Egyptian-listed companies and their impact on firm performance and financial distress in the context of an emerging market such as that of Egypt. Design/methodology/approach – To assess the level of CG practices at a given firm, the current study constructs a corporate governance index (CGI) which consists of four dimensions: disclosure and transparency, composition of the board of directors, shareholders’ rights and investor relations and ownership and control structure. Based on a sample of 86 non-financial firms listed on the Egyptian Exchange, the effects of CG on performance and financial distress are assessed. Tobin’s Q is used to assess corporate performance. At the same time, the Altman Z-score is used as a financial distress indicator, as it measures financial distress inversely. The bigger the Z-score, the smaller the risk of financial distress. Findings – The overall score of the CGI, on average, suggests that the quality of CG practices within Egyptian-listed firms is relatively low. The results do not support the positive association between CG practices and financial performance. In addition, there is an insignificant negative relationship between CG practices and the likelihood of financial distress. The current study also provides evidence that firm-specific characteristics could be useful as a first-pass screen in determining firm performance and the likelihood of financial distress. Research limitations/implications – The sample size and time frame of our analysis are relatively small; some caution would be needed before generalizing the results to the entire population. Practical implications – The findings may be of interest to those academic researchers, practitioners and regulators who are interested in discovering the quality of CG practices in a developing market such as that of Egypt and its impact on financial performance and financial distress. Originality/value – This paper extends the existing literature, in the Egyptian context in particular, by examining firm performance and the risk of financial distress in relation to the level of CG mechanisms adopted.
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Vestari, Mekani, and Dessy Noor Farida. "Analisis Rasio-Rasio Dan Ukuran Keuangan, Prediksi Financial Distress, Dan Reaksi Investor." AKRUAL: Jurnal Akuntansi 5, no. 1 (October 21, 2014): 26. http://dx.doi.org/10.26740/jaj.v5n1.p26-44.
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AbstractThe purpose of this paper is to investigate financial ratios and financial measurements that can predict financial distress. This study also examined investor reaction. To proved the effect for the long period this study not only examined the effect of independent variables per year to the prediction of financial distress, but also examined the average for five years.Using logistic regression the results showed that there are four financial ratios that can predict financial distress. Business risk and firm size is not proven to predict financial distress. Using Kruskall-Wallis test this study also proved that investors can predict financial distress.
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Ruxanda, Gheorghe, Cătălina Zamfir, and Andreea Muraru. "PREDICTING FINANCIAL DISTRESS FOR ROMANIAN COMPANIES." Technological and Economic Development of Economy 24, no. 6 (December 14, 2018): 2318–37. http://dx.doi.org/10.3846/tede.2018.6736.
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Using a moderately large number of financial ratios, we tried to build models for classifying the companies listed on the Bucharest Stock Exchange into low and high risk classes of financial distress. We considered four classification techniques: Support Vector Machines, Decision Trees, Bayesian logistic regression and Fisher linear classifier, out of which the first two proved to have the highest prediction accuracy. Classifiers were trained and tested on randomly drown samples and on four different databases built starting from the initial financial indicators. As the literature related to the topic on Romanian data is very scarce, our study, by using a variety of methods and combining feature selection and principal components analysis, brings a new approach to predicting financial distress for Romanian companies.
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Thim, Chan Kok, Yap Voon Choong, and Chai Shin Nee. "Factors affecting financial distress: The case of Malaysian public listed firms." Corporate Ownership and Control 8, no. 4 (2011): 345–51. http://dx.doi.org/10.22495/cocv8i4c3art3.
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A sample of 101 companies is selected randomly from Bursa Malaysia during the period 2005-2009 where two models are used to analyze the relationships between financial distress and firms’ characteristics and risk. The dependent variables are long-term debt to total equity ratio and short-term debt to total equity ratio. The independent variables are profitability, liquidity, firm size, solvency, growth and risk. Size is found to be significant and has a positive relationship with financial distress. Interest coverage ratio has a positive relationship with financial distress, while growth of operating profits has a negative relationship with financial distress. Corporate managers should use these indicators to detect early signs of financial distress and take innovative actions to prevent such occurrences.
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Nguyen Khac Quoc, Bao. "Incentives for Financial Risk Management in Vietnamese Enterprises: A Study on Their Determinants." Journal of Asian Business and Economic Studies 22, no. 02 (April 1, 2015): 85–101. http://dx.doi.org/10.24311/jabes/2015.22.2.02.
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This study aims to assess the factors affecting the incentives for financial risk management in Vietnamese enterprises. By employing multivariable binary logistic regression, the author examines the relationship between hedging decisions for firms’ financial risks and their determinants, namely financial distress costs, tax, agency cost of debt, capital-market imperfections and growth opportunity, hedge substitutes, level of managerial utility, level of government influence, and size of firms. The results demonstrate that hedging decisions for financial risks have a positive correlation with costs of financial distress and managerial utility, and a negative correlation with government influence. These findings are agreeable to empirical results of previous researches that work out on the same case.
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Nilasari, Agustina. "PENGARUH KINERJA KEUANGAN, RISK BASED CAPITAL, UKURAN PERUSAHAAN DAN MAKROEKONOMI TERHADAP FINANCIAL DISTRESS." Jurnal Ekonomi Bisnis dan Kewirausahaan 10, no. 1 (April 29, 2021): 55. http://dx.doi.org/10.26418/jebik.v10i1.44793.
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ABSTRACTThis research intends to examine the effect of insurance company financial ratios, namely solvency margin ratio, risk based capital, firm size, inflation and exchange rate on the estimated financial distress of life insurance companies. As well as general public listed on the Indonesia Stock Exchange from 2015 to 2019. This research is important considering that there have been cases of default by insurance companies. The research information in this research is secondary data obtained in the annual report which is sourced from BEI website and insurance company websites. The sample technique in this research is a purposive sampling technique, there are 35 samples that meet the standards to become samples. Insurance companies experiencing financial distress are determined based on the non-manufacturing Altman Z-score method. Multiple linear regression is the research technique chosen by researchers. This research results in the conclusion that only the firm size variable has an influence on financial distress estimates. The independent variables are able to explain the financial distress variable as much as 32.8%, the deficiency as much as 67.2%, which illustrates the variables that cannot be taken into account in the analysis of this study. ABSTRAKRiset ini bermaksud untuk menelaah pengaruh rasio keuangan perusahaan asuransi yakni solvency margin ratio (SMR), risk based capital (RBC), ukuran perusahaan (UK), inflasi (INF) serta nilai tukar (NT) terhadap perkiraan timbulnya keadaan financial distress perusahaan asuransi jiwa serta umum yang tercatat pada Bursa Efek Indonesia dari rentang waktu 2015 sampai 2019. Penelitian ini penting mengingat adanya kasus gagal bayar perusahaan asuransi. Informasi penelitian di dalam riset ini merupakan data sekunder yang didapatkan pada annual report yang bersumber dari website BEI serta website perusahaan asuransi. Teknik sampel di dalam riset ini merupakan teknik purposive sampling, terdapat 35 sampel yang memenuhi standar untuk menjadi sampel. Perusahaan asuransi yang mengalami financial distress ditentukan berdasarkan metode Altman Z-score non manufaktur. Regresi linier berganda menjadi teknik penelitian yang dipilih oleh peneliti. Riset ini menghasilkan kesimpulan bahwa hanya variabel ukuran perusahaan (UK) yang ada pengaruh terhadap perkiraan financial distress. Variabel bebas mampu memaparkan variabel financial distress sebanyak 32,8%, kekurangan sebanyak 67,2% digambarkan variabel yang tidak dapat diperhitungkan di dalam analisis penelitian ini.
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Ermar, Fikri Hakim, and Suhono Suhono. "Pengaruh RGEC (Risk Profile, Good Corporate Governance Earning, Capital) terhadap Financel Distress." Owner 5, no. 1 (February 1, 2021): 107–18. http://dx.doi.org/10.33395/owner.v5i1.320.
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This study aims to determine the effect of RGEC (Risk Profile, Good Corporate Governance, Earnings and Capital) on Financial Distress in banks listed on The Indonesia Stock Exchange (IDX) for the period of 2016-2019. The sample data used is the result of the purposive sampling technique and the samples declared worthy to be utilized are 21 banks. During the study conducted, the method was adopted which is a method of logistic regression analysis using SPSS 25 program aid. The results of the research show that the variables that are known can affect the Financial Distress is Return On Asset affect negatively and significantly. Meanwhile, variables that do not affect Financial Distress are Non-Performing Loan (NPL), Loan to Deposit Ratio, Good Corporate Governance, and Capital Adequacy Ratio. Simultaneously Non Performing Loans, Loan to Deposit Ratio, Good Corporate Governance, Return on Assets and Capital Adequacy Ratio have a significant effect on Financial Distress.