Search results
1 – 10 of 34Tutun Mukherjee, Pinki Gorai and Som Sankar Sen
This study aims to analyse the following: first, the financial performance of General Insurance Re (GIC Re) using performance ratios (PRs); second, the uniformity of different…
Abstract
Purpose
This study aims to analyse the following: first, the financial performance of General Insurance Re (GIC Re) using performance ratios (PRs); second, the uniformity of different financial performance indicators of GIC Re; third, the internal growth capacity of GIC Re; and finally, the likelihood of GIC Re going into financial distress.
Design/methodology/approach
As a sample, GIC Re, the lion shareholder in Indian Reinsurance Industry has been considered in the present study. All the necessary data have been extracted from the secondary sources over a time period of 16 years. The financial performance of GIC Re is assessed using five standard ratios, and the uniformity of different financial performance indicators of GIC Re has been examined using Kendall’s Coefficient of Concordance (W). To assess the internal growth capacity of GIC Re internal growth rate has been used, and the likelihood of GIC Re going into financial distress is analysed using multivariate discriminant approach, namely, modified Altman’s Z-score model and logit analysis technique, namely, Ohlson’s O-score model.
Findings
The results exhibit that financial performance of GIC Re is somewhat satisfactory over a few considerable areas. However, no notable degree of uniformity has been observed amongst the varied financial performance indicators, namely, performance ratio, expense ratio, return on assets, risk retention ratio and combined ratio of GIC Re. The results also reveal GIC Re is lacking ability of growing internally. Moreover, there remains a significant possibility of GIC Re going into financial distress in the near future and so.
Originality/value
This study is one of the first empirical research studies in India that examines the financial performance of GIC Re from different perspectives.
Details
Keywords
This paper aims to examine the empirical relationship between firm-level characteristics and the variability of the average portfolio returns of distressed firms. The…
Abstract
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.
Details
Keywords
The authors study stock and option grants around abrupt performance declines for continuing CEOs and find that firms facing abrupt financial declines grant more options than…
Abstract
Purpose
The authors study stock and option grants around abrupt performance declines for continuing CEOs and find that firms facing abrupt financial declines grant more options than stock, while firms facing operational decline grant more stock than options. Firms making these adjustments just prior to performance declines outperform those that do not for three years following the decline and are less likely to engage in asset restructuring. To establish causality, the authors exploit compensation changes instigated by FAS 123R accounting regulation in 2005 that mandated stock option expensing. The result is robust to numerous tests, including rebalancing of incentives and CEO turnover. The paper aims to discuss these issues.
Design/methodology/approach
To establish causality, the authors exploit compensation changes instigated by FAS 123R accounting regulation in 2005 that mandated stock option expensing.
Findings
Firms making these adjustments just prior to performance declines outperform those that do not for three years following the decline and are less likely to engage in asset restructuring. The result is robust to numerous tests, including rebalancing of incentives and CEO turnover.
Originality/value
Several studies examine the relationship between poor performance and compensation of newly appointed CEOs. But firms regularly employ retention or incentive plans when experiencing distress to prevent critical employees from leaving when they are most needed (Goyal and Wang, 2017). Employee turnover results in a loss of continuity coupled with high search and training costs for replacement personnel. Beneish et al. (2017) find that 57 percent of CEOs associated with intentional misreporting retain their jobs, implying the costs of removing CEOs is high, especially if the incumbent CEO has a strong track record relative to industry peers prior to the period before the misreporting begins. The board fires the CEO if future firm value under the CEO is expected to be lower than under the best alternative CEO less adjustment costs (e.g. search costs, severance pay).
Details
Keywords
This study seeks to explore developments in corporate creditworthiness before and after ownership events.
Abstract
Purpose
This study seeks to explore developments in corporate creditworthiness before and after ownership events.
Design/methodology/approach
The paper uses the Blockholders database of Dlugosz, Fahlenbrach, Gompers, and Metrick, and three credit quantities, and deploys a standard event study methodology to examine the relation to corporate creditworthiness.
Findings
The paper discovers that ownership‐construction is generally associated with prior‐ and post‐improvement in creditworthiness, while a block‐destruction is typically surrounded by deterioration in corporate creditworthiness. The paper also finds proper evidence for a relation between the construction or destruction of managerial block and future developments in corporate creditworthiness. The paper further realizes that outside shareholders exhibit higher impact than inside block‐holders on later variations in credit risk.
Research limitations/implications
The paper is unable to conduct further robustness checks with structural credit methodologies due to the reduced number of valid observations.
Originality/value
Market participants can utilize the conclusions to better predict future trends in corporate creditworthiness.
Details
Keywords
Loan default risk or credit risk evaluation is important to financial institutions which provide loans to businesses and individuals. Loans carry the risk of being defaulted. To…
Abstract
Purpose
Loan default risk or credit risk evaluation is important to financial institutions which provide loans to businesses and individuals. Loans carry the risk of being defaulted. To understand the risk levels of credit users (corporations and individuals), credit providers (bankers) normally collect vast amounts of information on borrowers. Statistical predictive analytic techniques can be used to analyse or to determine the risk levels involved in loans. This paper aims to address the question of default prediction of short-term loans for a Tunisian commercial bank.
Design/methodology/approach
The authors have used a database of 924 files of credits granted to industrial Tunisian companies by a commercial bank in the years 2003, 2004, 2005 and 2006. The naive Bayesian classifier algorithm was used, and the results show that the good classification rate is of the order of 63.85 per cent. The default probability is explained by the variables measuring working capital, leverage, solvency, profitability and cash flow indicators.
Findings
The results of the validation test show that the good classification rate is of the order of 58.66 per cent; nevertheless, the error types I and II remain relatively high at 42.42 and 40.47 per cent, respectively. A receiver operating characteristic curve is plotted to evaluate the performance of the model. The result shows that the area under the curve criterion is of the order of 69 per cent.
Originality/value
The paper highlights the fact that the Tunisian central bank obliged all commercial banks to conduct a survey study to collect qualitative data for better credit notation of the borrowers.
Propósito
El riesgo de incumplimiento de préstamos o la evaluación del riesgo de crédito es importante para las instituciones financieras que otorgan préstamos a empresas e individuos. Existe el riesgo de que el pago de préstamos no se cumpla. Para entender los niveles de riesgo de los usuarios de crédito (corporaciones e individuos), los proveedores de crédito (banqueros) normalmente recogen gran cantidad de información sobre los prestatarios. Las técnicas analíticas predictivas estadísticas pueden utilizarse para analizar o determinar los niveles de riesgo involucrados en los préstamos. En este artículo abordamos la cuestión de la predicción por defecto de los préstamos a corto plazo para un banco comercial tunecino.
Diseño/metodología/enfoque
Utilizamos una base de datos de 924 archivos de créditos concedidos a empresas industriales tunecinas por un banco comercial en 2003, 2004, 2005 y 2006. El algoritmo bayesiano de clasificadores se llevó a cabo y los resultados muestran que la tasa de clasificación buena es del orden del 63.85%. La probabilidad de incumplimiento se explica por las variables que miden el capital de trabajo, el apalancamiento, la solvencia, la rentabilidad y los indicadores de flujo de efectivo.
Hallazgos
Los resultados de la prueba de validación muestran que la buena tasa de clasificación es del orden de 58.66% ; sin embargo, los errores tipo I y II permanecen relativamente altos, siendo de 42.42% y 40.47%, respectivamente. Se traza una curva ROC para evaluar el rendimiento del modelo. El resultado muestra que el criterio de área bajo curva (AUC, por sus siglas en inglés) es del orden del 69%.
Originalidad/valor
El documento destaca el hecho de que el Banco Central tunecino obligó a todas las entidades del sector llevar a cabo un estudio de encuesta para recopilar datos cualitativos para un mejor registro de crédito de los prestatarios.
Palabras clave
Curva ROC, Evaluación de riesgos, Riesgo de incumplimiento, Sector bancario, Algoritmo clasificador bayesiano.
Tipo de artículo
Artículo de investigación
Details
Keywords
Kaylene Zaretzky and J. Kenton Zumwalt
Earlier research found that firms with the highest distress risk have low book‐to‐market (B/M) ratios and low returns. This paper aims to examine the robustness of those's results…
Abstract
Purpose
Earlier research found that firms with the highest distress risk have low book‐to‐market (B/M) ratios and low returns. This paper aims to examine the robustness of those's results and provide further evidence that high distress‐risk firms do not enjoy the same high returns earned by high B/M firms and that distress risk is unlikely to explain the Fama and French high‐minus‐low (HML) B/M factor.
Design/methodology/approach
A distress‐risk measure, distressed‐minus‐solvent (DMS), is calculated and a range of zero investment distress‐risk trading strategies is investigated. Value‐ and equal‐weighted portfolios are examined both with negative book‐equity firms and without. These most distressed firms have low or negative B/M values and would either not be included in the Fama and French sample or included in the low B/M portfolio.
Findings
The paper finds that the DMS factor is negative and significant, and none of the zero investment strategies earns significantly positive returns.
Research limitations/implications
The findings suggest that exposure to distress risk does not earns investors a positive risk premium. It appears that over the period examined, market inefficiencies drive the market value and returns of high distress‐risk firms.
Originality/value
The distress‐risk premium is shown to be negative and, therefore, cannot be driven by bankruptcy risk alone. The negative premium is not consistent with a financial distress explanation for the Fama and French HML factor.
Details
Keywords
Arun Upneja and Michael C. Dalbor
Examines the capital structure decisions of restaurant firms. Hypothesizes that these decisions are based upon a financial “pecking‐order” as well as the position of the firm in…
Abstract
Examines the capital structure decisions of restaurant firms. Hypothesizes that these decisions are based upon a financial “pecking‐order” as well as the position of the firm in the financial growth cycle. Using ratios from publicly‐traded restaurant firms in the USA and ordinary least squares regression models, the results tend to support the notion that both the pecking‐order and the financial growth cycle influence financing decisions. However, the results also indicate that there may be separate factors affecting long‐term and short‐term debt decisions made by restaurant managers.
Details
Keywords
Aigbe Akhigbe, Anna D. Martin and Laurence J. Mauer
The purpose of this paper is to investigate whether a non-monotonic relationship may exist between financial distress and foreign exchange (FX) exposure. The authors hypothesize…
Abstract
Purpose
The purpose of this paper is to investigate whether a non-monotonic relationship may exist between financial distress and foreign exchange (FX) exposure. The authors hypothesize that firms with higher FX exposures are those with the lowest levels of financial distress because the costs of hedging exceed the benefits and those with highest levels of financial distress due to the conflict of interest between shareholders and bondholders.
Design/methodology/approach
The methodology allows for the possibility of a non-monotonic relation between financial distress and FX exposure for firms known to have ex-ante exposures. The approach is to include a Black-Scholes-Merton financial distress measure and standard accounting-based financial distress measures.
Findings
The results support the hypothesis of a non-monotonic relationship between financial distress and exposure; companies with the lowest and highest levels of financial distress are willing to bear greater FX exposures.
Originality/value
The authors examine whether a non-monotonic relationship may exist between distress and FX exposure. Intuition for this non-monotonic relationship is provided by Stulz (1996) as he describes the risk management practices of firms with low, medium, and high default probabilities.
Details
Keywords
This study updates the literature review of Jones (1987) published in this journal. The study pays particular attention to two important themes that have shaped the field over the…
Abstract
Purpose
This study updates the literature review of Jones (1987) published in this journal. The study pays particular attention to two important themes that have shaped the field over the past 35 years: (1) the development of a range of innovative new statistical learning methods, particularly advanced machine learning methods such as stochastic gradient boosting, adaptive boosting, random forests and deep learning, and (2) the emergence of a wide variety of bankruptcy predictor variables extending beyond traditional financial ratios, including market-based variables, earnings management proxies, auditor going concern opinions (GCOs) and corporate governance attributes. Several directions for future research are discussed.
Design/methodology/approach
This study provides a systematic review of the corporate failure literature over the past 35 years with a particular focus on the emergence of new statistical learning methodologies and predictor variables. This synthesis of the literature evaluates the strength and limitations of different modelling approaches under different circumstances and provides an overall evaluation the relative contribution of alternative predictor variables. The study aims to provide a transparent, reproducible and interpretable review of the literature. The literature review also takes a theme-centric rather than author-centric approach and focuses on structured themes that have dominated the literature since 1987.
Findings
There are several major findings of this study. First, advanced machine learning methods appear to have the most promise for future firm failure research. Not only do these methods predict significantly better than conventional models, but they also possess many appealing statistical properties. Second, there are now a much wider range of variables being used to model and predict firm failure. However, the literature needs to be interpreted with some caution given the many mixed findings. Finally, there are still a number of unresolved methodological issues arising from the Jones (1987) study that still requiring research attention.
Originality/value
The study explains the connections and derivations between a wide range of firm failure models, from simpler linear models to advanced machine learning methods such as gradient boosting, random forests, adaptive boosting and deep learning. The paper highlights the most promising models for future research, particularly in terms of their predictive power, underlying statistical properties and issues of practical implementation. The study also draws together an extensive literature on alternative predictor variables and provides insights into the role and behaviour of alternative predictor variables in firm failure research.
Details
Keywords
Md Jahidur Rahman, Hongtao Zhu and Sihe Chen
This study aims to investigate the relationship between corporate social responsibility (CSR) and financial distress and the moderating effect of firm characteristics, auditor…
Abstract
Purpose
This study aims to investigate the relationship between corporate social responsibility (CSR) and financial distress and the moderating effect of firm characteristics, auditor characteristics and the Coronavirus disease 2019 (Covid-19) in China.
Design/methodology/approach
The research question is empirically examined on the basis of a data set of 1,257 Chinese-listed firms from 2011 to 2021. The dependent variable is financial distress risk, which is measured mainly by Z-score. CSR score is used as a proxy for CSR. Propensity score matching, two-stage least square and generalized method of moments are adopted to mitigate the potential endogeneity issue.
Findings
This study reveals that CSR can reduce financial distress. Specifically, results show an inverse relationship between CSR and financial distress, more significantly in non-state-owned enterprises, firms with non-BigN auditor and during Covid-19. The results are consistent and robust to endogeneity tests and sensitivity analyses.
Originality/value
This study enriches the literature on CSR and financial distress, resulting in a more attractive corporate environment, improved financial stability and more crisis-resistant economies in China.
Details