Since 2008, the world has been in recession. As daily news outlets report, this crisis has prompted many small businesses and large corporations to file for bankruptcy, which has grave global social implications. Despite government intervention and incentives to stimulate the economy that have put nations in hundreds of billions of dollars of debt, and have reduced the prime rates to almost zero, efforts to combat the increase in unemployment rate as well as the decrease in discretionary income have been troublesome. It is a vicious cycle: consumers are apprehensive of spending due to the instability of their jobs and ensuing personal financial problems; businesses are weary from the lack of revenue and are forced to tighten their operations which likely translates to layoffs; and so on. Cautious movement of cash flows are rooted in and influenced by the psychology of the players (stakeholders) of the game (society). Understandably, the complexity of this economic fallout is the subject of much attention. And while the markets have recovered much of the lost ground as of late, there is still great opportunity to learn about all the possible factors of this recession, in anticipation of and bracing for one more downturn before we emerge from this crisis. In fact, there is no time like today more appropriate for research in bankruptcy prediction because of its relevance, and in an age where documentation is highly encouraged and often mandated by law, the amount and accessibility of data is paramount – an academic’s paradise! The main objective of this thesis was to develop a model supported by Data Envelopment Analysis (DEA) to predict the likelihood of failure of US companies in the retail-apparel industry based on information available from annual reports – specifically from financial statements and their corresponding Notes, Management’s Discussion and Analysis, and Auditor’s Report. It was hypothesized that the inclusion of variables which reflect managerial decision-making and economic factors would enhance the predictive power of current mathematical models that consider financial data exclusively. With a unique and comprehensive dataset of 85 companies, new metrics based on different aspects of the annual reports were created then combined with a slacks-based measure of efficiency DEA model and modified layering classification technique to capture the multidimensional complexity of bankruptcy. This approach proved to be an effective prediction tool, separating companies with a high risk of bankruptcy from those that were healthy, with a reliable accuracy of 80% – an improvement over the widely-used Altman bankruptcy model having 70%, 58% and 50% accuracy when predicting cases today, from one year back and from two years back, respectively. It also provides a probability of bankruptcy based on a second order polynomial function in addition to targets for improvement, and was designed to be easily adapted for analysis of other industries. Finally, the contributions of this thesis benefit creditors with better risk assessment, owners with time to improve current operations as to avoid failure altogether, as well as investors with information on which healthy companies to invest in and which unhealthy companies to short.

Since 2008, the world has been in recession. As daily news outlets report, this crisis has prompted many small businesses and large corporations to file for bankruptcy, which has grave global social implications. Despite government intervention and incentives to stimulate the economy that have put nations in hundreds of billions of dollars of debt, and have reduced the prime rates to almost zero, efforts to combat the increase in unemployment rate as well as the decrease in discretionary income have been troublesome. It is a vicious cycle: consumers are apprehensive of spending due to the instability of their jobs and ensuing personal financial problems; businesses are weary from the lack of revenue and are forced to tighten their operations which likely translates to layoffs; and so on. Cautious movement of cash flows are rooted in and influenced by the psychology of the players (stakeholders) of the game (society). Understandably, the complexity of this economic fallout is the subject of much attention. And while the markets have recovered much of the lost ground as of late, there is still great opportunity to learn about all the possible factors of this recession, in anticipation of and bracing for one more downturn before we emerge from this crisis. In fact, there is no time like today more appropriate for research in bankruptcy prediction because of its relevance, and in an age where documentation is highly encouraged and often mandated by law, the amount and accessibility of data is paramount – an academic’s paradise! The main objective of this thesis was to develop a model supported by Data Envelopment Analysis (DEA) to predict the likelihood of failure of US companies in the retail-apparel industry based on information available from annual reports – specifically from financial statements and their corresponding Notes, Management’s Discussion and Analysis, and Auditor’s Report. It was hypothesized that the inclusion of variables which reflect managerial decision-making and economic factors would enhance the predictive power of current mathematical models that consider financial data exclusively. With a unique and comprehensive dataset of 85 companies, new metrics based on different aspects of the annual reports were created then combined with a slacks-based measure of efficiency DEA model and modified layering classification technique to capture the multidimensional complexity of bankruptcy. This approach proved to be an effective prediction tool, separating companies with a high risk of bankruptcy from those that were healthy, with a reliable accuracy of 80% – an improvement over the widely-used Altman bankruptcy model having 70%, 58% and 50% accuracy when predicting cases today, from one year back and from two years back, respectively. It also provides a probability of bankruptcy based on a second order polynomial function in addition to targets for improvement, and was designed to be easily adapted for analysis of other industries. Finally, the contributions of this thesis benefit creditors with better risk assessment, owners with time to improve current operations as to avoid failure altogether, as well as investors with information on which healthy companies to invest in and which unhealthy companies to short.

<p>År 2007 gick 5 791 svenska företag i konkurs. Företagskonkurser kan få svåra ekonomiska konsekvenser för företagens intressentkrets. Utöver den uppenbara ekonomiska förlusten för företagsledningen och ägarna drabbas även andra intressenter såsom bolagets kreditgivare, leverantörer, kunder, staten och naturligtvis bolagets anställda. Följderna av en företagskonkurs kan dock mildras om företagets intressenter får en möjlighet att förbereda sig. Genom att förutse ett företags konkurs ges intressenterna en chans att vidta nödvändiga åtgärder för att skydda sina intressen. Traditionellt sett har finansiella nyckeltal allena utgjort verktygen för att förutsäga konkurser. Vi utgår från finansiella nyckeltal i denna studie, men adderar även förvaltningsberättelsen som förklaringsvariabel.</p><p>Syftet med denna studie är att avgöra huruvida förvaltningsberättelsen kan bidra till de finansiella nyckeltalen när det gäller att förutse ett företags konkurs samt ta reda på huruvida det finns en motvilja att i förvaltningsberättelsen rapportera uppriktigt om en dyster framtid. För att utreda detta har vi valt att studera hur variablerna balansomslutning, soliditet, kassalikviditet, bruttovinstmarginal, räntabilitet på eget kapital samt förvaltningsberättelsens innehåll påverkar konkursrisken. Detta främst med hjälp av logistisk regression.</p><p>Resultaten visar att alla finansiella nyckeltal enskilt är signifikanta inom ett 95-procentigt konfidensintervall och förvaltningsberättelsen är enskilt signifikant inom ett 90-procentigt konfidensintervall. Enligt den logistiska regressionsmodellen, vilken testar alla variabler gemensamt, är balansomslutningen, soliditeten och bruttovinstmarginalen signifikanta mått för att förutsäga konkurser. Alla finansiella nyckeltal visar även negativa samband med konkursrisken, vilket innebär att ökade värden på dessa nyckeltal minskar konkurssannolikheten. De förvaltningsberättelser som inte bara nämner möjligheter utan även framtida risker är också signifikanta i sammanhanget. Sådana förvaltningsberättelser ökar konkursrisken fem gånger.</p><p>Genom att eliminera förvaltningsberättelsen ur den logistiska regressionen sjönk modellens totala förklaringsgrad, vilket indikerar att förvaltningsberättelsen bidrar till konkursförutsägelser. Bidraget kunde dock vara större om framtidsutsikterna uttrycktes på ett mer sanningsenligt sätt, detta mot bakgrund i att förvaltningsberättelser som inte bara behandlar möjligheter utan även risker och osäkerhetsfaktorer var signifikanta enligt den logistiska regressionsmodellen och ökade konkursrisken markant. Vi drar också slutsatsen att det verkar finnas en motvilja att rapportera sanningsenligt om framtiden när denna inte ser ljus ut.</p> / <p>In the year of 2007, 5 791 Swedish companies went bankrupt. A corporate failure may have severe economical consequences on its environment. Besides the obvious setback to the management and owners when the company goes bankrupt, creditors, suppliers, customers, the government and of course the company’s employees are all affected. The consequences of corporate failures may be mitigated however if the company’s stakeholders get an opportunity to prepare themselves. By predicting corporate failures, stakeholders get a chance to take necessary measures to protect their interests in the company. Traditionally financial ratios have been used exclusively as tools to predict corporate failures. In this study we use financial ratios as a starting-point but to those we also add the companies’ management reports as a variable to predict corporate failures.</p><p>The purpose of this paper is to examine to what extinct the companies’ management reports contribute to the financial ratios when it comes to predicting corporate failures and also investigate whether there is an aversion towards reporting truthfully in the management’s reports about a depressing future. In order to examine this we chose to study how variables such as balance sheet total, solidity, quick asset ratio, gross profit margin, and return on shareholders’ equity as well as the management’s report affect the probability of corporate bankruptcy. These relationships have been investigated mainly through the use of logical regression.</p><p>The results of this study show that all of the financial ratios on their own are significant when it comes to predicting corporate failures within a confidence interval of 95 percent, while the management’s report is significant within a confidence interval of 90 percent. The logical regression, which investigates the significance of the variables jointly, indicates that the balance sheet total, the solidity and the gross profit margin are significant tools to predict bankruptcy. All ratios included in the model show negative coefficients with the probability of bankruptcy, which means that superior values of those ratios reduce the risk of bankruptcy. Managements’ reports that not only process future opportunities but also discuss future risks are significant when it comes to predicting corporate failures. Those management’s reports increase the probability of corporate failures five times.</p><p>By eliminating management’s reports from our logical regression the model’s ability to classify firms as failure companies or surviving companies decreased. This indicates that the management’s report in fact do contribute to the bankruptcy predictability. However, the contribution could have been greater if corporate management would express their thoughts about the company’s future in a more truthful manner. This considering that management’s reports that discuss risks as well as possibilities are significant according to the logical regression model and considerably increased the risk of corporate failure. We also concluded that there seams to be an aversion towards reporting truthfully about an unfortunate future.</p>

År 2007 gick 5 791 svenska företag i konkurs. Företagskonkurser kan få svåra ekonomiska konsekvenser för företagens intressentkrets. Utöver den uppenbara ekonomiska förlusten för företagsledningen och ägarna drabbas även andra intressenter såsom bolagets kreditgivare, leverantörer, kunder, staten och naturligtvis bolagets anställda. Följderna av en företagskonkurs kan dock mildras om företagets intressenter får en möjlighet att förbereda sig. Genom att förutse ett företags konkurs ges intressenterna en chans att vidta nödvändiga åtgärder för att skydda sina intressen. Traditionellt sett har finansiella nyckeltal allena utgjort verktygen för att förutsäga konkurser. Vi utgår från finansiella nyckeltal i denna studie, men adderar även förvaltningsberättelsen som förklaringsvariabel. Syftet med denna studie är att avgöra huruvida förvaltningsberättelsen kan bidra till de finansiella nyckeltalen när det gäller att förutse ett företags konkurs samt ta reda på huruvida det finns en motvilja att i förvaltningsberättelsen rapportera uppriktigt om en dyster framtid. För att utreda detta har vi valt att studera hur variablerna balansomslutning, soliditet, kassalikviditet, bruttovinstmarginal, räntabilitet på eget kapital samt förvaltningsberättelsens innehåll påverkar konkursrisken. Detta främst med hjälp av logistisk regression. Resultaten visar att alla finansiella nyckeltal enskilt är signifikanta inom ett 95-procentigt konfidensintervall och förvaltningsberättelsen är enskilt signifikant inom ett 90-procentigt konfidensintervall. Enligt den logistiska regressionsmodellen, vilken testar alla variabler gemensamt, är balansomslutningen, soliditeten och bruttovinstmarginalen signifikanta mått för att förutsäga konkurser. Alla finansiella nyckeltal visar även negativa samband med konkursrisken, vilket innebär att ökade värden på dessa nyckeltal minskar konkurssannolikheten. De förvaltningsberättelser som inte bara nämner möjligheter utan även framtida risker är också signifikanta i sammanhanget. Sådana förvaltningsberättelser ökar konkursrisken fem gånger. Genom att eliminera förvaltningsberättelsen ur den logistiska regressionen sjönk modellens totala förklaringsgrad, vilket indikerar att förvaltningsberättelsen bidrar till konkursförutsägelser. Bidraget kunde dock vara större om framtidsutsikterna uttrycktes på ett mer sanningsenligt sätt, detta mot bakgrund i att förvaltningsberättelser som inte bara behandlar möjligheter utan även risker och osäkerhetsfaktorer var signifikanta enligt den logistiska regressionsmodellen och ökade konkursrisken markant. Vi drar också slutsatsen att det verkar finnas en motvilja att rapportera sanningsenligt om framtiden när denna inte ser ljus ut. / In the year of 2007, 5 791 Swedish companies went bankrupt. A corporate failure may have severe economical consequences on its environment. Besides the obvious setback to the management and owners when the company goes bankrupt, creditors, suppliers, customers, the government and of course the company’s employees are all affected. The consequences of corporate failures may be mitigated however if the company’s stakeholders get an opportunity to prepare themselves. By predicting corporate failures, stakeholders get a chance to take necessary measures to protect their interests in the company. Traditionally financial ratios have been used exclusively as tools to predict corporate failures. In this study we use financial ratios as a starting-point but to those we also add the companies’ management reports as a variable to predict corporate failures. The purpose of this paper is to examine to what extinct the companies’ management reports contribute to the financial ratios when it comes to predicting corporate failures and also investigate whether there is an aversion towards reporting truthfully in the management’s reports about a depressing future. In order to examine this we chose to study how variables such as balance sheet total, solidity, quick asset ratio, gross profit margin, and return on shareholders’ equity as well as the management’s report affect the probability of corporate bankruptcy. These relationships have been investigated mainly through the use of logical regression. The results of this study show that all of the financial ratios on their own are significant when it comes to predicting corporate failures within a confidence interval of 95 percent, while the management’s report is significant within a confidence interval of 90 percent. The logical regression, which investigates the significance of the variables jointly, indicates that the balance sheet total, the solidity and the gross profit margin are significant tools to predict bankruptcy. All ratios included in the model show negative coefficients with the probability of bankruptcy, which means that superior values of those ratios reduce the risk of bankruptcy. Managements’ reports that not only process future opportunities but also discuss future risks are significant when it comes to predicting corporate failures. Those management’s reports increase the probability of corporate failures five times. By eliminating management’s reports from our logical regression the model’s ability to classify firms as failure companies or surviving companies decreased. This indicates that the management’s report in fact do contribute to the bankruptcy predictability. However, the contribution could have been greater if corporate management would express their thoughts about the company’s future in a more truthful manner. This considering that management’s reports that discuss risks as well as possibilities are significant according to the logical regression model and considerably increased the risk of corporate failure. We also concluded that there seams to be an aversion towards reporting truthfully about an unfortunate future.

Magistro darbe išanalizuota ir susisteminta Lietuvos ir užsienio autorių mokslinė literatūra įmonių bankroto klausimais. Aptartos įmonių bankroto atsiradimo priežastys bei pasekmės šalies ekonomikai. Išanalizuoti bankroto prognozavimo metodai teoriniu aspektu. Praktinėje dalyje atlikta statistinių duomenų lyginamoji analizė ir apibendrinimas. Aptartos kitimo priežastys ir pasekmės. Atliktas bankrutuojančių įmonių bankroto priežasčių įvertinimas. Tiriamojoje dalyje atlikta bankroto prognozavimo modelių analizė, kuria remiantis išskirti tinkamiausi bankroto prognozavimo metodai. Atlikus analizę patvirtinta iškelta hipotezė, kad nėra vieno bankroto prognozavimo modelio tinkančio visoms įmonėms. / In the master‘s thesis, the scientifie literature of Lithuanian and forein authors, regarding bankruptcy of the companies, is analyzed and systematized. The reasons of the bankrupcy, orginating in the company and their consequences for the country‘s economics and discussed. The methods of the bankruptcy forecasting, according to the theoretical aspect are analyzes. In the practical part, the comparative analysis of the statistical data and generalization is carried out. The reasons and consequences of the alteration are disputed as well. In addition, the evaluation of the bankruptcy reasons of the next door to the bankruptcy companies is performed. In the empirical part of the present paper, the bankruptcy forecasting are distinguished. After analyzing, the raised hypothesis has proved out, that there is not a single particular model of the bankruptcy forecasting, which would suit all companies.

Magistro darbe išanalizuoti ir susisteminti Lietuvos bei užsienio autorių teoriniai ir praktiniai tyrimai, susiję su įmonių bankroto požymiais, priežastimis ir pasekmėmis. Išnagrinėti įvairūs bankroto grėsmės prognozavimo modeliai. Atlikta nuosekli bankrotus Lietuvoje reglamentuojančių įstatymų palyginamoji analizė. Apibendrinti dinaminiai šalies bankrotų skaičiaus pokyčiai. Taip pat įvertinti makroekonominių rodiklių bei bankrotų skaičiaus sąryšiai ir pateiktos prognozės. Atliktas bankrotų prognozavimo modelių tyrimas, kuriuo remiantis patvirtinta autorių suformuluota mokslinio tyrimo hipotezė, kad nėra vieno universalaus, tinkančio visoms įmonėms bankroto prognozavimo modelio. Remiantis atliktu tyrimu, išskirti tinkamiausi bankroto prognozavimo modeliai kiekvienai įmonių grupei. / There are analyzed and systematized theoretical and practical researches into evidences, reasons and results of companies’ bankruptcy conducted by various Lithuanian and foreign authors in this master’s final paper. There are explored various bankruptcy prediction models. There is made consistent comparable analysis of laws regulated Lithuanian bankruptcy. In this master’s final paper are summarized dynamic alterations of state’s bankruptcy number. Also there are estimated relations between macro economical indicators and bankruptcy number and there are proposed prognoses. It is made research of bankruptcy prediction models according which is confirmed by paper’s authors formulated scientific research hypothesis that there is no one universal, suitable for all companies bankruptcy prediction model. According to made research there are discerned most appropriate bankruptcy prediction models for every group of companies.

Some of the largest United States bankruptcies of publicly-traded non-financial firms have occurred within the last decade. The continuing need to improve bankruptcy prediction has generated numerous research studies utilizing various prediction models. The purpose of this study is to test the usefulness of the multiple discriminant, probit, and artificial neural network (ANN) models in predicting bankruptcy in the United States textile-related industry. Financial data is examined for 47 bankrupt and 104 non-bankrupt publicly-traded firms in the textile-related industry during the time period 1998-2004, which includes the events of the Asian currency crisis and increased competition from China. Models developed by Altman (1968), Altman (1983), Zmijewski (1984) are compared to ANNs based upon each of these models. A comparison to an ANN including all of the ratios of the previous models and variables for firm size and domestic sales is also made. The Altman (1968) model and ANN 68 model are found to have the higher predictive power for one and two years prior to bankruptcy, respectively, for bankrupt firms. The ANN 84 model and the ANN 83 model have the highest correct classification results for nonbankrupt firms for the entire time period. Solvency and leverage variables appear to have the most impact on the bankruptcy prediction of textile-related firms. The additional variables of firm size and domestic sales are not found to improve the predictive accuracy. This study supports the continued use of the original Altman (1968) model for predicting bankruptcy in a manufacturing industry. Simultaneous utilization of the ANN 83 model to predict nonbankrupt firms is also suggested since the majority of the Altman (1968) variables can be used and the higher potential for improved predictability. This study may be extended to years after 2004 with consideration given to quarterly information, NAICs codes, and leverage variable alternatives.

This master thesis deals with bankruptcy prediction models for construction companies doing business in Czech Republic. Terms important for understanding the issue are defined in the theoretical part. In analytical part, there are five current bankruptcy prediction models tested on the analysed sample and resulted accuracy compared with original ones. On the basis of knowledges acquired, there is developed a brand-new bankruptcy prediction model.

Bakalauro baigiamajame darbe pritaikyti įvairūs bankroto prognozavimo modeliai bei apskaičiuoti dažniausiai naudojami mokumo ir pelningumo rodikliai, neįeinantys į modelius, tačiau turintys didelę įtaką bankroto prognozėms. / Various bankruptcy prediction models are adapted in this bachelor thesis. Generally used solvency and profitability rates, that are not part of models, but have an impact for bankrupt prediction, had been calculated.

This diploma thesis deals with the creation of a bankruptcy model for the manufacturing industry in the Czech Republic using logit analysis. The theoretical part defines the concept of bankruptcy model, financial distress and financial health of the company. This section is focused on the influence of macroeconomics on the accuracy of these models, a look into their history and description of selected models. The practical part of the thesis is initially focused on determining the reliability of selected bankruptcy models, and then a new bankruptcy model is compiled.