No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Corporate Governance in Distressed Firms
Abstract
Fiduciary Duties of Managers and DirectorsFrequency and Timing of Management and Board ChangesManagement CompensationChanges in Ownership and Control
... Private limited liability companies would face higher risk, as they would have less share capital to lose compared with public limited liability companies (Esteve-Pérez et al., 2010). From what concern the indicators of firm's financial performance, we consider the most relevant and effective indicators in highlighting current and prospective conditions of financial distress that refer to the different methodological proposals, from the pioneer works on the topic (Fitzpatrick, 1931Fitzpatrick, , 1932 Smith & Winakor, 1930) since the more recent contributions (Altman & Hochkiss, 2006; Amendola, Restaino, & Sensini, 2011; Balcaen & Ooghe, 2006; Laitinen & Suvas, 2013; Ravi Kumar & Ravi, 2007; Xie, Shi, & Wu, 2008). To anticipate the results, our findings reveal several differences in the factors determining firms' way out with respect to the exit routes. ...
... The predictor data-base for the years of interest (2004–2009) is elaborated starting from the financial statements of each firm included in the sample, for a total of 8030 balance sheets. In particular, we compute nv = 24 indicators selected as potential predictors among the most relevant in highlighting current and prospective conditions of financial distress (Altman & Hochkiss, 2006; Dimitras, Zanakis, & Zopoudinis, 1996). The selected indicators reflect the main aspects of the firms' structure such as profitability, solvency and liquidity. ...
This paper investigates the influence and the effect of micro-economic indicators and firm-specific factors on different states of financial distress. In particular, a competing risks model is estimated taking into account the differences among variables leading firms to exit the market through bankruptcy, liquidation and inactivity. The determinants of financial distress for any exit route are identified on the basis of the influence on the hazard ratios of the significant variables selected for each state. Furthermore, the predictive performance of the competing-risks model over the single-risk framework is evaluated, with respect to different time windows, by means of some accuracy measures. The results reached on a sample of Italian firms provide support for the hypothesis that the factors influencing firms' way out strongly depend on the exit routes and highlighting the need to distinguish among them by means of a multiple-state approach.
... Also, firms have access to financial resources by reducing the perceived bankruptcy risk (Altman and Hotchkiss 2010). Because creditors have not enough information about firms and their capacity to return the credit, they expect more reliable firms to undertake actions that are signals of their higher capacity to pay back (Srinivasan, Lilien, and Sridhar 2011). ...
The objective of this research is to evaluate the effect of the economic recession on the performance of firms located in science or technological parks. Compared to off-park firms, we propose that under an economic crisis park benefits are more noticeable, since firms located inside parks have less resource restraints and access to external sources of information and knowledge. Moreover, we observe that as firms invest on internal R&D, they tend to reinforce these park benefits. Empirical evidence gathered data on employment and sales from 2007 to 2012 for the group of firms which participated in the Spanish Technological Innovation Panel. The results confirm the positive role played by science and technology park locations under economic downturn environments, especially when firms investing in internal R&D.
... Tel.: +48713204150. business condition that are further used to induce a mathematical model using past observations ( Altman & Hotchkiss, 2010 ). There are different issues that are associated with the bankruptcy prediction. ...
... However, due to the uncertainty of business environment and strong competition, even companies with perfect operation mechanism have the possibility of business failure and financial bankruptcy. So whether listed companies financial distress can be forecasted effectively and timely is related to companies' development, numerous investors' interest, and the order of capital market123. Most topical studies have adopted a multiple-variable approach to the prediction of financial distress by combining accounting and nonaccounting data in a variety of statistical formulas4567. ...
Bankruptcy prediction is an important problem facing financial decision support for stakeholders of firms, including auditors, managers, shareholders, debt-holders, and potential investors, as well as academic researchers. Popular discourse on financial distress forecasting focuses on developing the discrete models to improve the prediction. The aim of this paper is to develop a novel hybrid financial distress model based on combining various statistical and machine learning methods. Then multiple attribute decision making method is exploited to choose the optimized model from the implemented ones. Proposed approaches have also been applied in Iranian companies that performed previous models and it can be consolidated with the help of the hybrid approach.
... Various methods have been employed to measure bank risk in the existing literature. Those methods include some alternative measures of firm risk such as subordinated debt spread (Krishnan et al., 2006) and expected default frequency calculated by an option pricing model (Altman and Hotchkiss, 2005). In addition, the CDS premium or spread has been increasingly popular as a simple indicator of bank credit risk. ...
Using the panel analysis of non-stationarity in idiosycratic and common component method, we decompose Credit Default Swap (CDS) premium data of 11Korean banks into common factors and idiosyncratic shocks. We find that the CDS premium of all 11 banks is mostly explained by one common factor. We also find that the common factor of the banksâ CDS premium is mainly affected by the level and the volatility of stock market prices in developed markets and oil prices. It suggests that the Korean banking industry is susceptible to foreign shocks due to the heavy dependency of the Korean economy on export. We also find that a structural break in the common part of CDS premium occurred in mid-2007, implying that the exposure of credit risk in Korean banks jumped up after the 2007 financial crisis.
... The first Altman's model, however, applies only to companies listed on the capital markets, as one of the independent variables ( ) contains the market value of equity capital. For this reason, in 1983, Altman modified his model, replacing this value with the book value of equity (Altman & Hotchkiss, 2005). As a result, Z-score may also be used to analyze the non-public entities. ...
The aim of this article is to analyze and evaluate the usability of discri-minant models in predicting bankruptcy for companies listed on NewConnect. This market was established in 2007 and operates as an alternative trading system next to Warsaw Stock Exchange S.A., which in practice means that its regulatory re-gime in relation to issuers and listed companies is not as strict as the one applica-ble to the main market, therefore shares of small and medium-size businesses, including start-ups, can be listed on NewConnect. In this paper, discriminant mod-els are used to analyse the financial situation of four companies removed from trading on NewConnect due to bankruptcy, Perfect Line S.A., Promet S.A., In-wazjaPC S.A. and Budostal-5 S.A. The analysis is based on three models: Altman's model for emerging markets, as well as two models of the highest predictive ability according to P. Antonowicz's research, Z7 INEPAN model developed in the Polish Academy of Sciences and E. Mączyńska's model, developed by Polish scientists and adapted to the Polish economy. The results confirm that these models are a valua-ble tool in assessing the financial condition of enterprises and allow for bankrupt-cy forecasting. Their application to companies listed on NewConnect, however,
... More moderate scores may be easily misclassified (Moriarty, 1979). In the early 2000s, Altman amended the formula to allow its application to certain situations not originally included in the original sample set (Altman, 2006). ...
Altman's Z, a multiple discriminant analysis bankruptcy model using commonly accepted cutoff criteria, may provide a useful decision rule to predict financial distress in firms operating in a wide variety of industries. In this study, we outline the construction and interpretation of the Z-Score and apply it to several pairs of firms (N=17) from a variety of specialty retail industries spanning two consecutive years. Past research indicates that Altman's Z predicted future financial distress in 90 percent of the firms studied. In this study, all but two of the bankruptcies (94 percent) would have been accurately predicted. Despite some criticism of the model's efficacy, two firms were misclassified yet later revealed potential financial distress.
... The CF, SIZE and LEV variables are considered endogenous because these variables could be affected by the investment decisions. The financial distress variable is considered exogenous because investment has not been included as an explanatory variable of financial distress in the literature (Mossman et al., 1998; Altman and Hotchkiss, 2006). For the endogenous variables, first or deeper lags have been used as instruments. ...
This paper analyzes the influence of financial distress on the investment behavior of companies. The analysis includes companies from Germany, Canada, Spain, France, Italy, UK and USA, which cover a wide spectrum of different institutional environments. The methodology used is panel data estimation using the Generalized Method of Moments (System-GMM), thereby allowing control of both unobservable heterogeneity and the problems of endogeneity in explanatory variables. The results show that the influence of financial distress on investment is different according to the investment opportunities available to companies. So, companies in difficulties with fewer opportunities have the greatest propensity to under-invest, while firms in difficulties with better opportunities do not present different investment behavior than healthy companies.
... Insolvency and bankruptcy have been studied in the areas of Accounting and Finance for several decades. Most of these studies address these elements under different perspectives; either trying to predict them [2, 3, 33, 34], or analysing the processes that occur during an insolvency crisis or bankruptcy [1, 16]. As a side note, in the literature, insolvency, failure and bankruptcy usually appear as synonyms; however they refer to different moments. ...
In 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.
... Such a traditional position, however, has been disputed in recent years, with an increasing number of scholars claiming that the Bankruptcy Act of 1978 fueled a major shift in -4 the market's perception about bankruptcy (Sheppard, 1995; Tavakolian 1995; Delaney, 1998:3). The key issue here is that the Code does not require a company to be insolvent before filing for reorganization under Chapter 11 (e.g., Johnson et al, 1986; Sheppard, 1995; Tavakolian 1995; Altman and Hotchkiss, 2005:28). 1 As a result, U.S. bankruptcy law offered managers a mechanism that allows their organizations, almost at will, to fight nearly every undesirable financial obligation (Sheppard, 1995). Not surprisingly, there have been many cases where firms use Chapter 11 in a non-traditional way (Johnson et al, 1986; Delaney, 1998). ...
We investigate whether the stock market differentiates between firms that file bankruptcy petitions for strategic reasons, and those that file for financial distress-related, i.e., non-strategic reasons. We find that the market is unable to distinguish between strategic and non-strategic Chapter 11s in both the pre-event and event periods. However, we also document an asymmetric longer-term market reaction to bankruptcy announcements conditional on type of filing with the market underreacting in the case of non-strategic bankruptcies but overreacting in the strategic case as indicated by subsequent positive abnormal returns. For non-strategic bankruptcies, we find a significant post-event drift of around -29% over the subsequent 12-months. Conversely, in the case of strategic bankruptcies, we report a reversal in the stock return pattern with a significant risk-adjusted abnormal return of around 29% in the 6-month period following the Chapter 11 announcement date. We also demonstrate that our findings are robust to alternative explanations documented in prior literature like the momentum effect, industry, or financial distress. Complementary tests reveal that firm-specific information, trading costs and investor level of sophistication help explain our puzzling results; the market appears to be biased in its treatment of bankruptcy filings.
... Given cross-section data of firms, it is common to estimate a constant default probability using the logistic or probit models. A leading example is the " O-score " of Ohlson (1980); see Altman and Hotchkiss 2006 for a survey. As pointed out by Shumway (2001), a static model is inappropriate for forecasting bankruptcy because firm characteristics may change from time to time. ...
In this paper, we propose a regime-switching intensity model to predict the occurrences of default events. Individual firm's default intensity function, i.e., the instantaneous default probability function, is determined by both observable risks factors and an unobservable regime indicator. We provide estimation algorithm when the regime indicator follows the discrete-time Markovian process. The empirical study on U.S. listed corporations suggests three key criteria when specifying the intensity function. They are systematically and objectively chosen observable risk factors, a common frailty variable, and the regime-dependent risk exposure to firm's leverage proxy or observable risk factors. Comparing to classical default intensity models, the regime-switching intensity model with these components has better performance in the in-sample fit and in the out-of sample prediction ability.
... The term strategic bankruptcy is sometimes used in the literature to describe such situations, which are 1 A new Bankruptcy Code was introduced in the U.S. on October 2005. According to Altman and Hotchkiss (2005), the new Code is more " creditor-friendly " than its predecessor and thus filing a strategic bankruptcy might be harder nowadays. However, we only consider the Oct/1979 -Oct/2005 period, so our results are not affected by the potential impact of this regulatory change. ...
This paper explores the market response to two apparently similar but in fact very different firm-specific bad-news events: 1) filing a strategic Chapter 11, and 2) filing a financially-motivated Chapter 11. We find that the market is unable to distinguish between the two in both the pre-event, and bankruptcy filing event, periods. In particular, in both cases, prices drop by around a half in risk-adjusted terms in the one-year pre-event window, falling a further 25% around the event date. On the other hand, we find that the subsequent market reaction to the announcement of strategic and non-strategic Chapter 11s is quite different. For non-strategic bankruptcies, there is a post-event drift of around -29% over the subsequent 12-months. Conversely, in the case of strategic bankruptcies, we uncover a reversal in the stock return pattern: risk-adjusted abnormal returns are now of 29% in the 6-month period following the event date. As such, filing for Court protection against creditors for non-strategic reasons seems to be increasingly perceived by the market as bad news over time, while filing a strategic bankruptcy becomes recognized over time as a positive news event. Complementary analysis reveals that a mix of behavioral biases, information uncertainty and the trading environment may well help explain our puzzling results.
The standard theory of coherent risk measures fails to consider individual institutions as part of a system which might itself experience instability and spread new sources of risk to the market participants. In compliance with an approach adopted by Shapley and Shubik (1969), this paper proposes a cooperative market game where agents and institutions play the same role can be developed. We take into account a multiple institutions framework where some of them jointly experience distress events in order to evaluate their individual and collective impact on the remaining institutions in the market. To carry out this analysis, we define a new risk measure (SCoES), generalising the Expected Shortfall of Acerbi (2002) and we characterise the riskiness profile as the outcome of a cost cooperative game played by institutions in distress (a similar approach was adopted by Denault 2001). Each institution's marginal contribution to the spread of riskiness towards the safe institutions in then evaluated by calculating suitable solution concepts of the game such as the Banzhaf--Coleman and the Shapley--Shubik values.
Günümüz koşulları göz önüne alındığında işletmelerin hedeflerini gerçekleştirebilmeleri için finansal açıdan güçlü olmaları gerekmektedir. Bu nedenle finansal başarısızlıklarının tahmin edilmesi, işletmelerin gelecekte oluşabilecek finansal riskleri tespit etmeleri ve gerekli önlemleri almaları bakımından oldukça önemlidir. Çalışmada, Borsa İstanbul’da 2010-2013 döneminde kesintisiz olarak işlem gören 143 imalat sanayi şirketinin yıllık bilanço ve gelir tablosu verilerinden yararlanılarak işletmelerin finansal başarılı ve başarısız olma durumları tahmin edilmeye çalışılmıştır. Araştırmada Veri Madenciliği ve Lojistik Regresyon Analizi yöntemleri kullanılmıştır. 2013 yılı baz alınarak bir yıl, iki yıl ve üç yıl öncesinin tahmin edilmesine yönelik modeller geliştirilmiş ve modellerin sınıflandırma doğrulukları başka bir ifadeyle modellerin tahmin gücü karşılaştırılmıştır. Analiz sonucunda, işletmelerin finansal başarılı ve başarısız olma durumlarını tahmin etmek için oluşturulan tüm modellerde 2012 yılı tahmin gücü en başarılı yıl olarak saptanmıştır.
Anahtar Kelimeler: Finansal Başarı/Başarısızlık, Veri Madenciliği, Lojistik Regresyon Analizi
The going principle activity, unanimously recognized as a basic principle of accounting - financial reports in the two accountancy reporting systems IFRS and GAAP, has become more and more emphasized and studied in the specialists activity in the field as a follow up of resounding bankruptcies and general economic crisis. The capacity of an enterprise to continue its activity from a financial exercise to another, given the conditions of respecting the going principle, represents a basic foundation for investment decisions in the case of stakeholders or third parties who, under a form or another wish to have first a clear image over the financial status of the interested company. The general goal in view was constituted by the foundation, from a technical point of view of the going principle, next to the identification through a case study; of a practical diagnose solution of the going principle, by applying the Altman bankruptcy prognosis pattern for an enterprise in the Romanian furniture industry. The conclusions we arrived at emphasize the fact that the pattern is fully applicable in our case in two specific variants, and the usefulness of the Altman pattern application for evaluating the going principle is implicit.
In the next period we expect changes in credit risk management system at banks in BiH. A standardized approach will be replaced by an approach based on internal rating. Economic and social environment as well as the current level of knowledge will be a challenge for the implementation of internal rating in our society and at individual banks level. This paper will explain functionality of internal rating based approach model in Bosnia and Herzegovina environment. Our aim is to identify the challenges to implement this model and respond to question: „what amount of expected losses Bosnia banks have in their portfolio according to internal rating based approach?”. This paper could serve as a framework for domestic banks to determine the level of expected losses, provisions in banks portfolio, the level of unexpected losses, ie. necessary capital for conducting business, the implementation of internal methodologies. Simple models should have primacy over complex ones because of simplicity of the hole financial sector in Bosnia. The work will assess the basic risk parameters for implementation internal rating (PDs, LGDs, EAD) in BiH. Thus, the parameters, although conservative convinced us in the sufficient level of capital and provision looking at aggregate level to cover credit risk. But we should take into account the fact that some banks due to different risk profile can have different results.
Bankruptcy, especially during an economic crisis, is a common phenomenon. In the adverse changing economic conditions, economic activities become a chal-lenge. Only strong individuals are able to survive the economic fluctuations, while others are eliminated from the market. The integrated models are used in predicting bankruptcy. These models are often designed on the basis of financial indicators. Some of these models use similar financial indicators, in many cases using the same ones. The present study deals with the evaluation of the sector of animal slaughtering and processing in the period 2000-2011, as well as the eval-uation of the causes of business failure in the sector, and the comparison of bank-rupt companies in the sector.
We ask whether public financial aid reduces small businesses’ credit constraints. To answer the question, we analyze a policy
of bank loans made from subsidized funds. Extensions of this large program are plausibly exogenous and help identify its effects.
Using firm-level data, we find that the program substantially increases debt financing without substitution between subsidized
and unsubsidized finance. Returns on subsidized debt are significantly above its market cost, with no subsequent surge in
default risk. We interpret this as evidence that targeted firms are credit-constrained and underline the implied welfare differences
between upfront financial aid and public guarantees.
The variable selection is a challenging task in statistical analysis. In many real situations, a large number of potential predictors are available and a selection among them is recommended. For dealing with this problem, the automated procedures are the most commonly used methods, without taking into account their drawbacks and disadvantages. To overcome them, the shrinkage methods are a good alternative. Our aim is to investigate the performance of some variable selection methods, focusing on a statistical procedure suitable for the competing risks model. In this theoretical setting, the same variables might have different degrees of influence on the risks due to multiple causes and this has to be taken into account in the choice of the "best" subset. The proposed procedure, based on shrinkage techniques, is evaluated by means of empirical analysis on a data-set of financial indicators computed from a sample of industrial firms annual reports.
that we can use to find out impending problems in the company are prediction models, i.e. models that are able to assess the financial health of the company and to warn owners of the company and company’ business partners before the threat of bankruptcy. Financial analysis can be ex-post and ex-ante. In the literature we can find several names used for the ex-ante financial analysis, such as financial health prediction, forecast financial health, early warning systems, etc. In the article is used the term prediction of financial health. There are many methods on which are based the construction of prediction models and in the article authors further specified discriminant analysis.
This paper tests to what extent the Hong and Stein (1999) model explains the stock price performance of firms filing for Chapter 11 bankruptcy. In line with the model’s main prediction, I find that the market severely misprices (correctly prices) the bankrupt firms for which information is likely to diffuse slowly (rapidly) across investors. My key finding is robust to a range of alternative methods for adjusting for risk and different periods for computing the abnormal stock returns. My innovative framework provides an acid test of the predictive ability of the Hong and Stein (1999) model, with my results suggesting that it offers important insight into the workings of financial markets, even in the very extreme setting I consider.
Because financial crises are characterized by dangerous rare events that occur more frequently than those predicted by models with finite variances, we investigate the underlying stochastic process generating these events. In the 1960s Mandelbrot [Mandelbrot B (1963) J Bus 36:394-419] and Fama [Fama EF (1965) J Bus 38:34-105] proposed a symmetric Lévy probability distribution function (PDF) to describe the stochastic properties of commodity changes and price changes. We find that an asymmetric Lévy PDF, L, characterized by infinite variance, models several multiple credit ratios used in financial accounting to quantify a firm's financial health, such as the Altman [Altman EI (1968) J Financ 23:589-609] Z score and the Zmijewski [Zmijewski ME (1984) J Accounting Res 22:59-82] score, and models changes of individual financial ratios, ΔX(i). We thus find that Lévy PDFs describe both the static and dynamics of credit ratings. We find that for the majority of ratios, ΔX(i) scales with the Lévy parameter α ≈ 1, even though only a few of the individual ratios are characterized by a PDF with power-law tails X(i)(-1-α) with infinite variance. We also find that α exhibits a striking stability over time. A key element in estimating credit losses is the distribution of credit rating changes, the functional form of which is unknown for alphabetical ratings. For continuous credit ratings, the Altman Z score, we find that P(ΔZ) follows a Lévy PDF with power-law exponent α ≈ 1, consistent with changes of individual financial ratios. Estimating the conditional P(ΔZ|Z) versus Z, we demonstrate how this continuous credit rating approach and its dynamics can be used to evaluate credit risk.
ResearchGate has not been able to resolve any references for this publication.