Bankruptcies have been a sensitive topic all around the world for over 50 years. From their research, the authors have found that only a few bankruptcy studies have been conducted in Sweden and even less on the topic of bankruptcy prediction models. This thesis investigates the performance of the Altman, Ohlson and Zmijewski bankruptcy prediction models. This research investigates all Swedish companies during the years 2017 and 2018.  This study has the intention to shed light on some of the most famous bankruptcy prediction models. It is interesting to explore the predictive abilities and usability of those three models in Sweden. The second purpose of this study is to create two models from the most significant variable out of the three models studied and to test its prediction power with the aim to create two models designed for Swedish companies.  We identified a research gap in terms of Sweden, where bankruptcy prediction models have been rather unexplored and especially with those three models. Furthermore, we have identified a second research gap regarding the time period of the research. Only a few studies have been conducted on the topic of bankruptcy prediction models post the financial crisis of 2007/08.  We have conducted a quantitative study in order to achieve the purpose of the study. The data used was secondary data gathered from the Serrano database. This research followed an abductive approach with a positive paradigm. This research has studied all active Swedish companies between the years 2017 and 2018. Finally, this contributed to the current field of knowledge on the topic through the analysis of the results of the models on Swedish companies, using the liquidity theory, solvency and insolvency theory, the pecking order theory, the profitability theory, the cash flow theory, and the contagion effect. The results aligned with the liquidity theory, the solvency and insolvency theory and the profitability theory. Moreover, from this research we have found that the Altman model has the lowest performance out of the three models, followed by the Ohlson model that shows some mixed results depending on the statistical analysis. Lastly, the Zmijewski model has the best performance out of the three models. Regarding the performance and the prediction power of the two new models were significantly higher than the three models studied.

[pt] Os estudos de modelos de previsão de falência tiveram seu início há quase 90 anos, sempre com o intuito de ser uma ferramenta de gestão útil para analistas e gestores das empresas. Embora as primeiras pesquisas sejam antigas, o assunto continua atual. Diversos setores da economia passaram, ou passam, por crises ao longo do tempo e não foi diferente para a indústria de aviação. Nesse contexto, o presente trabalho usou dados históricos de indicadores financeiros das empresas aéreas americanas de um período de três décadas para elaborar quatro modelos de previsão de falência e comparar suas performances preditivas com o Modelo Z-Score. Todas as elaborações foram calibragens do Modelo Z-Score, usando técnicas de simulação e estatística. Duas usaram Análise Discriminante Múltipla (MDA) e duas utilizaram Bootstrap junto com MDA. Um par de cada método utilizou as variáveis originais do Modelo Z-Score e o outro par apresentou sugestão de novo conjunto de variáveis. Os resultados mostraram que o modelo de previsão mais preciso, com 75,0 porcento de acerto na amostra In-Sample e 79,2 porcento na Out-of-Sample, utilizou o conjunto original de variáveis e as técnicas Bootstrap e MDA. / [en] Studies of bankruptcy prediction models started almost 90 years ago, with the intention of being a useful management tool for analysts and managers. Although the first researches are ancient, the subject remains current. Several sectors of the economy have experienced, or are experiencing, crises over time and the aviation industry is no exception. In this context, the present work used historical data of financial indicators of American airlines over a period of three decades to develop four models of bankruptcy forecast and compared their predictive performances with the Z-Score Model. All proposed models were calibrations of the Z-Score model, using simulation and statistical techniques. Two models were generated using Discriminant Analyzes Multiple (MDA) and two using Bootstrap along with MDA. A pair of each method used the original variables of the model s Z-Score and the other pair presented a novel set of variables. Results showed that the most accurate forecasting model, with 75.0 percent accuracy in-sample and 79.2 percent out-of-sample, used the original variables of the model s Z-Score and the Bootstrap e MDA techniques.

Problem: I dagens Sverige har det blivit tämligen enkelt att starta upp ett eget aktiebolag och till följd av detta har antalet konkurser ökat. Konkursprediktion med hjälp av finansiella nyckeltal är ett beforskat område och sträcker sig tillbaka till början av 1960-talet. Altmans Z- scoremodeller är de mest tillämpade modellerna att förutspå en konkurs. Problematiken är att Z-scoremodellerna inte genererar lika hög träffsäkerhet i Sverige då modellerna är konstruerade i USA som härstammar från en annan redovisningstradition och tillämpar ett annat regelverk. Syfte: Studiens syfte är att testa Altmans Z ́-scoremodell utifrån den kontinentala redovisningstraditionen på 2000-talet. Vidare är syftet att modifiera Z ́-scoremodellen genom att utveckla modellen i enlighet med svensk redovisning. Metod: Studien bygger på en kvantitativ metod med en deduktiv forskningsansats och utifrån ett positivistiskt perspektiv. Analysen utgår från Altmans Z ́-scoremodell och en multipel diskriminantanalys. Slutsats: Studien visar att de finansiella nyckeltalen kan förutspå en konkurs på ett tillförlitligt sätt med hjälp av studiens egenutvecklade modell ZPP-scoremodellen. Modellen har en träffsäkerhet på 88 procent ett år före konkurs på svenska tillverkande företag. Emellertid visar studien att Altmans Z ́-scoremodell inte är tillförlitlig utan måste modifieras i enlighet med svensk redovisning för att kunna erhålla en välfungerande och tillförlitlig modell. / Problem: Today in Sweden it has become equally easy to start up a private limited company and as a result of this, the number of bankruptcies increased. Bankruptcy prediction using financial ratios is a well-researched area and extends back to the early 1960s. The most used models are Altman's Z-scoremodels. The problem is that the Z-scoremodels do not generate as high precision in Sweden because the models are designed in the United States, which is originating from a different accounting tradition and applies a different set of regulations.Purpose: The study aims to test the Altman Z'-score model on the continental accounting tradition in the 2000s. Furthermore, it intends to modify the Z'-score model by developing the model in accordance with Swedish accounting.Method: This paper is based on a quantitative method with a deductive research approach and from a positivistic perspective. The analysis is based on the Altman Z' –scoremodel and multiple discriminant analysis.Conclusion: This paper shows that financial ratios can predict a bankruptcy reliably using the papers developed model ZPP -scoremodel. The model has a precision of 88 percent a year before the bankruptcy of Swedish manufacturing companies. However, the paper shows that Altman Z' -scoremodel is not reliable without being modified in accordance with Swedish accounting in order to obtain an efficient and reliable model.

This study investigates the prediction of firms’ health in terms of bankruptcy and non-bankruptcy based on the sentiments extracted from the earnings calls. Bankruptcy prediction has long been a critical topic in the world of accounting and finance. A firm's economic health is the current financial condition of the firm and is crucial to its stakeholders such as creditors, investors, shareholders, partners, and even customers and suppliers. Various methodologies and strategies have been proposed in research domain for predicting company bankruptcy more promptly and accurately. Conventionally, financial risk prediction has solely been based on historic financial data. However, an increasing number of finance papers also analyze textual data during the last few years. Company’s earnings calls are the key source of information to investigate the current financial condition and how the businesses are doing and what the expectations are for the next quarters. During the call, management offers an overview of recent performance and provide a guidance for the next quarter expectations. The earnings calls summary is provided by the management and can extract the CEO’s sentiments using sentiment analysis. In the last decade, Machine Learnings based techniques have been proposed to achieve accurate predictions of firms’ economic health. Even though most of these techniques work well in a limited context, on a broader perspective these techniques are unable to retrieve the true semantic from the earnings calls, which result in the lower accuracy in predicting the actual condition of firms’ economic health. Thus, state-of-the-art Machine Learnings and Deep Learnings techniques have been used in this thesis to improve accuracy in predicting the firms’ health from the earnings calls. Various machine learnings and deep learnings method have been applied on web-scraped earnings calls data-set, and the results show that LONG SHORT-TERM MEMORY (LSTM) is the best machine learnings technique as compared to the comparison set of models.

Bakgrund: Varje år går många företag i konkurs och detta innebär stora kostnader på kort sikt. Kreditgivare, ägare, investerare, borgenärer, företagsledning, anställda samt samhället är de som i störst utsträckning drabbas av detta. För att kunna bedöma ett företags ekonomiska hälsa är det därför en viktig del att kunna prognostisera risken för en konkurs. Till hjälp har vi olika konkursmodeller som har utvecklats sedan början av 1960-talet och fram till idag. Syfte: Att undersöka tre internationella konkursmodeller för att se om dessa kan tillämpas på svenska företag samt jämföra träffsäkerheten från vår studie med konkursmodellernas originalstudier. Metod: Undersökningen är baserad på en kvantitativ forskningsstrategi med en deduktiv ansats. Urvalet grundas på företag som gick i konkurs år 2014. Till detta kommer också en kontrollgrupp bestående av lika stor andel friska företag att undersökas. Det slumpmässiga urvalet kom att bestå av 30 konkursföretag samt 30 friska företag från tillverknings- och industribranschen. Teori: I denna studie undersöks tre konkursmodeller; Altman, Fulmer och Springate. Dessa modeller och tidigare forskning presenteras utförligare i teoriavsnittet. Dessutom beskrivs under teoriavsnittet några nyckeltal som är relevanta vid konkursprediktion. Resultat och slutsats: Modellerna är inte tillämpbara på svenska företag då resultaten från vår studie inte visar tillräcklig träffsäkerhet och är därför måste betecknas som otillförlitliga. / Background: Each year many companies go bankrupt and it is associated with significant costs in the short term. Creditors, owners, investors, management, employees and society are those that gets most affected by the bankruptcy. To be able to estimate a company’s financial health it is important to be able to predict the risk of a bankruptcy. To help, we have different bankruptcy prediction models that have been developed through time, since the 1960s until today, year 2015. Purpose: To examine three international bankruptcy prediction models to see if they are  applicable to Swedish business and also compare the accuracy from our study with each bankruptcy prediction models original study. Method: The study was based on a quantitative research strategy and also a deductive research approach. The selection was based on companies that went bankrupt in year 2014. Added to this is a control group consisting of healthy companies that will also be examined. Finally, the random sample consisted of 30 bankrupt companies and 30 healthy companies that belong to the manufacturing and industrial sectors. Theory: In this study three bankruptcy prediction models are examined; Altman, Fulmer and Springate. These models and also previous research in bankruptcy prediction are further described in the theory section. In addition some financial ratios that are relevant in bankruptcy prediction are also described. Result and conclusion: The models are not applicable in the Swedish companies.  The results of this study have not showed sufficient accuracy and they can therefore be regarded as unreliable.

Bakgrund och problemdiskussion: Idag är konkurser ett problem då många företag försätts i konkurs samt att de bidrar till konsekvenser som påverkar hela samhället. Byggföretag är hårt drabbade och det finns olika tillvägagångssätt, bland annat att genom olika modeller och nyckeltal, för att beräkna konkurser i förväg och ta åtgärder. Syfte: Syftet med studien är att jämföra och analysera fem olika konkursprognostiseringsmodeller och dess nyckeltal i de svenska byggföretagen, för att se om någon eller några modeller är tillämpbara. Syftet med studien är vidare att jämföra våra resultat med resultatet från den litauiska studien och se om vi får ett liknande resultat. Metod: Studien har använt ett kvantitativt tillvägagångssätt där data har samlats in från årsredovisningar för att sedan tillämpas i fem konkursprognostiseringsmodeller. Vidare har nyckeltalen granskats bland annat utifrån en regressionsanalys. Resultat och slutsats: Ingen av de fem modellerna är tillämpbara i de svenska byggföretagen då ingen av påvisar en tillräckligt hög träffsäkerhet som anses pålitlig. Med hjälp av nyckeltal kan man till hög grad säga hur väl ett företag mår och därför till viss sannolikhet säga huruvida företaget kommer gå i konkurs. / Background: When companies go bankrupt and they contribute to consequences that affect the entire society from different aspect. The construction sector is very affected line of business but there are different approaches for calculating bankruptcies in advance and measuring how well a business is. Purpose: The purpose of this study is to compare and analyze five different bankruptcy prediction models and their financial ratios in Swedish construction sector, to see if any or some models are applicable. Furthermore, the purpose of the study is also to compare our results with the results from the Lithuanian study and see if we get a similar result. Method: The study has used a quantitative approach where data has been collected from the companies’ annual financial reports and then applied in five bankruptcy prediction models. Results and conclusion: None of the five models are applicable in Swedish construction sector, as none of them shows high accuracy which is considered reliable.

The Master's Thesis analyzes in detail the company STUDENT AGENCY, k.s.. This thesis includes a financial analysis of the years 2008 - 2012, followed by a strategical analysis of STUDENT AGENCY'S current operations. All the gained information is synthesized with the SWOT analysis that creates the base for the author's recommendations regarding the business strategy. The Master's Thesis consists of the introduction, the theoretical section, the practical section and the conclusion. In the introduction the basic facts are explained and the motives for writing this thesis are described. The used methodology is described in the theoretical section and then applied on the company in the practical section. In the closure the summary of the findings is made.

Varje år går tusentals företag i konkurs, vilket innebär förluster för samhället i stort och för de intressenter som på något sätt kan förknippas till företaget. För banken som lånar ut krediter till företag som går i konkurs innebär det kreditförluster om det inte finns säkerheter som täcker lånet. Därför är behovet av tidiga varningssignaler av stor betydelse för intressenter. Syftet med detta arbete är att teoretiskt analysera och empiriskt pröva varningssignaler för konkurser samt förklara signaler om förestående konkurs i kreditbedömning. Studiens resultat visar att risker för konkurser kan upptäckas med hjälp av finansiella och icke-finansiella nyckeltal. Resultatet i denna studie visar att återbetalningsförmåga, vilket består av soliditet och likviditet är den viktigaste varningssignaler bland de finansiella nyckeltalen. Revisionsanmärkningar, bankens egna mätinstrument, erfarenhet och VD:ns ålder är de viktigaste varningssignalerna bland de icke-finansiella nyckeltalen. Resultatet visar även att dessa varningssignaler blir starkare desto närmare konkurs företaget är. / Every year thousands of firms file for bankruptcy, creating considerable loses for the society and stakeholders associated with the firm. A bankruptcy by a firm, that a bank have loaned money to, can also affect the bank considerably if there are not assets enough to cover the outstanding debt. Considering the negative consequences of a bankruptcy it is of paramount interest to be able to spot early warning signals. The study shows that bankruptcy risks can be detected with the help of the firm´s financial and non-financial key assessment indicators.  The purpose of this paper is to theoretically and empirically study warning signals of bankruptcies, in order to identify and explain the signals in the credit assessments before occurrence of the bankruptcy.  The result of this study shows that the refund assessment consisting of solidity and liquidity are the most important warning signals among the financial key assessment indicators. Remarks, the bank´s own measuring instrument, experience, and the CEO´s age are the most important warning signals among non-financial key assessment indicators. Additionally, results show that the warning signals become stronger the closer the company proceeds towards bankruptcy.

The thesis deals with the recognition of the financial situation of „Hospodářské obchodní družstvo Jabloňov-Ruda“ in years 2012 – 2016. The first part of the thesis contains theoretic findings that are subsequently applied at the evaluation of the financial health of the analysed organization during the application of chosen methods of the strategic and financial analysis.On the basis of the total recognition of the financial situation of the agricultural co-operative, actions leading to improvements of an exist status are brought in.

This diploma thesis is focused on the evaluation of the efficiency of selected bankruptcy models in the Czech Republic. In the theoretical part the basic terminology and methodology of bankruptcy models creation are introduced. In addition are mentioned, model constraints, an overview of the indicators used, and information about model accuracy. This part also presents analyzed models and methods of assessing the reliability of bankruptcy models. In the practical part, the reliability of selected bankruptcy models is evaluated and a new bankruptcy model is built.