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 is concerned with developing a model to identify small-medium U.K. companies at risk of financial failure up to five years in advance. The importance of small companies in an economy, the impact of their failures, and the lack of failure research with respect to . this population, provided justification for this study. The research was undertaken in two stages. The first stage included a detailed description and discussion of the nature and role of small business in the UK economy, heir relevance, problems and Government involvement in this sector, together with literature review and assessment of past research relevant to this study. The second stage was involved with construction of the models using multiple discriminant analysis, applied to published accountancy data for two groups of failed and nonfailed companies. The later stage was performed in three parts : (1) evaluating five discriminant models for each of five years prior to failure; (2) testing the performance of each of the .five models over time on data not used . in their construction; (3) testing the discriminant models on a validation sample. The purpose was to establish the "best" discriminant model. "Best" was determined according to classification ability of the model and interpretation of variables. Finally a model comprising seven financial ratios measuring four aspects of a company's financial profile, such as profitability, gearing, capital turnover and liquidity was chosen. The model has shown to be a valid tool for predicting companies' health up to five years in advance. / Ministry of Higher Education and Scientific Research of the Iraqi Government.

No / This study examines the effect of board composition on the likelihood of corporate failure in the UK. We consider both independent and non-independent (grey) non-executive directors (NEDs) to enhance our understanding of the impact of NEDs' personal or economic ties with the firm and its management on firm performance. We find that firms with a larger proportion of grey directors on their boards are less likely to fail. Furthermore, the probability of corporate failure is lower both when firms have a higher proportion of grey directors relative to executive directors and when they have a higher proportion of grey directors relative to independent directors. Conversely, there is a positive relationship between the likelihood of corporate failure and the proportion of independent directors on corporate boards. The findings discussed in this study support the collaborative board model and the view that corporate governance reform efforts may have over emphasised the monitoring function of independent directors and underestimated the benefits of NEDs' affiliations with the firm and its management. (C) 2013 Elsevier Ltd. All rights reserved.

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.

Background: A public offering or "Initial Public Offering" means that a company is transferred from being unlisted to trading on a stock exchange. When a company is listed, the company needs to establish a prospectus. This document is meant to give potential investors information about the operations in the company with both historical financial data and more descriptive information. The prospectus should therefore contain all necessary information needed to make a well-founded assessment about the IPO. Historically IPOs have tended to overperform in the short term and have an underperformance in the long run compared with already listed companies. Purpose: The purpose of the study was to identify the general return patterns for IPOs in Sweden in both short-term and in the long run. The study also aims to investigate whether the company's prospectus published in connection with the IPO can explain these yield patterns. Methodology: The general return patterns have been calculated using the Buy and Hold Abnormal Return (BHAR) and Cumulative Abnormal Return (CAR) methods. The raw returns shown by the IPOs have been adjusted to the chosen reference index to determine whether an over- or underperformance has taken place. In addition, several multiple regressions have been conducted to determine whether selected variables can explain the abnormal return shown by IPOs. Conclusion: The study results shows that the initial return on the first day of the 2007-2014 period was an average of 2.82% for the study's selection of 45 public offerings from Stockholmsbörsen and First North. The IPOs showed a negative trend with an underperformance in the first three months. The result for the short term is thus not consistent with previous research in IPOs. In the long run, however, the study's selection shows an underperformance of -12.85% measured with BHAR and -24.13% with CAR. This result is consistent with previous studies in other markets. Furthermore, only one of the selected variables, the initial return, could to some extent (16.8%) explain the abnormal return for the first month. The other variables were not statistically significant in any of the studied periods. / Bakgrund: En börsintroduktion eller "Initial Public Offering" innebär att ett företag övergår från att vara onoterad till att handlas på en aktiebörs. I samband med att ett företag börsnoteras behöver företaget upprätta ett prospekt. Detta dokument ska ge potentiella investerare information om verksamheten av både beskrivande kvalitet och historiska finansiella data som kan kvantifieras av investeraren. Ett prospekt bör således innehålla all nödvändig information för att göra en välgrundad bedömning. Vidare har börsintroduktioner historiskt visat att dessa tenderar att överprestera på kort sikt och underpresterar på lång sikt jämfört med redan börsnoterade företag. Syfte: Syftet med studien var att identifiera generella avkastningsmönster för börsintroduktioner på kort- och lång sikt i Sverige. Studien ämnar även att undersöka om företagets prospekt som publiceras i samband med börsintroduktionen kan förklara dessa avkastningsmönster. Metod: De generella avkastningsmönstrena har beräknats med hjälp av metoden Buy and Hold Abnormal Return (BHAR) och Cumulative Abnormal Return (CAR). Avkastningen som börsintroduktionerna uppvisar har justerats till valt referensindex för att avgöra huruvida en över- eller underprestation har skett. Vidare har flertal multipla regressioner genomförts för att fastställa om utvalda variabler kan förklara den abnormala avkastningen som börsintroduktioner uppvisar. Slutsats: Studiens resultat visar att den initiala avkastningen första dagen under perioden 2007–2014 var i genomsnitt 2,82% för studiens urval på 45 stycken börsintroduktioner på Stockholmsbörsen och First North. Börsintroduktionerna visade på en negativ trend med en underprestation de första tre månaderna. Resultatet för kort sikt överensstämmer således inte med tidigare forskning inom börsintroduktioner. På lång sikt däremot uppvisar studiens urval en underavkastning på -12,85% mätt med BHAR och -24,13% med CAR. Detta resultat överensstämmer med tidigare studier på andra marknader. Vidare kunde endast en av de utvalda variablerna, den initiala avkastningen, till en viss grad (16,8%) förklara den abnormala avkastningen på en månad. De andra variablerna var inte statistiskt signifikanta i någon av undersökningsperioderna.

This thesis deals with the development, implementation and application of statistical modeling techniques which can be employed in the analysis of credit ratings. Credit ratings are one of the most widely used measures of credit risk and are relevant for a wide array of financial market participants, from investors, as part of their investment decision process, to regulators and legislators as a means of measuring and limiting risk. The majority of credit ratings is produced by the "Big Three" credit rating agencies Standard & Poors', Moody's and Fitch. Especially in the light of the 2007-2009 financial crisis, these rating agencies have been strongly criticized for failing to assess risk accurately and for the lack of transparency in their rating methodology. However, they continue to maintain a powerful role as financial market participants and have a huge impact on the cost of funding. These points of criticism call for the development of modeling techniques that can 1) facilitate an understanding of the factors that drive the rating agencies' evaluations, 2) generate insights into the rating patterns that these agencies exhibit. This dissertation consists of three research articles. The first one focuses on variable selection and assessment of variable importance in accounting-based models of credit risk. The credit risk measure employed in the study is derived from credit ratings assigned by ratings agencies Standard & Poors' and Moody's. To deal with the lack of theoretical foundation specific to this type of models, state-of-the-art statistical methods are employed. Different models are compared based on a predictive criterion and model uncertainty is accounted for in a Bayesian setting. Parsimonious models are identified after applying the proposed techniques. The second paper proposes the class of multivariate ordinal regression models for the modeling of credit ratings. The model class is motivated by the fact that correlated ordinal data arises naturally in the context of credit ratings. From a methodological point of view, we extend existing model specifications in several directions by allowing, among others, for a flexible covariate dependent correlation structure between the continuous variables underlying the ordinal credit ratings. The estimation of the proposed models is performed using composite likelihood methods. Insights into the heterogeneity among the "Big Three" are gained when applying this model class to the multiple credit ratings dataset. A comprehensive simulation study on the performance of the estimators is provided. The third research paper deals with the implementation and application of the model class introduced in the second article. In order to make the class of multivariate ordinal regression models more accessible, the R package mvord and the complementary paper included in this dissertation have been developed. The mvord package is available on the "Comprehensive R Archive Network" (CRAN) for free download and enhances the available ready-to-use statistical software for the analysis of correlated ordinal data. In the creation of the package a strong emphasis has been put on developing a user-friendly and flexible design. The user-friendly design allows end users to estimate in an easy way sophisticated models from the implemented model class. The end users the package appeals to are practitioners and researchers who deal with correlated ordinal data in various areas of application, ranging from credit risk to medicine or psychology.

This disertation is focused on financial analysis of economic activities of joint-stock company MAVE Jičín for accounting period 2011 - 2015. The goal of the financial analysis is an assessment of the company financial state. The disertation incorporates overview of financial analysis methods and describes financial statements, which are a source of informations for analysis. Selected elementary methods of financial analysis are used in the practical part of analysis. These are particularly horizontal analysis and vertical analysis, Net working capital, profitability ratios, liquidity, activity and leverage ratios, Du Pont equation, Altman Z-score, bankruptcy model IN95, the IN99 index and Rudolf Doucha Balance analysis II. The financial analysis results give an overview of developments in the financial situation of the joint-stock company MAVE Jičín and thereby provide information for company financial management.

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.

Intäkter är en väsentlig del av redovisningen och används för att fastställa de finansiella resultaten. Det är även ett betydelsefullt mått för intressenter som använder intäktsredovisningen för att bedöma företags finansiella prestation. År 2002 påbörjade IASB ett projekt för att utveckla en ny internationell intäktsstandard. Anledningen till detta var att öka jämförbarheten mellan olika företag och länder samt att utveckla ett mer konsekvent ramverk för intäktsredovisning. Svenska onoterade företag som klassificeras som större företag ska tillämpa det svenska regelverket K3, men har även möjlighet att följa det internationella regelverket IFRS genom att tillämpa den svenska rekommendationen RFR 2. Syftet med denna studie är att undersöka om skillnader uppstår mellan regelverken RFR 2/IFRS 15 och K3 vid redovisning av intäkter när hänsyn tas till inkomstbeskattning, utdelningsmöjligheter och nyckeltal. Syftet i studien är även att visa vilket regelverk som är mer fördelaktigt ur ett intressentperspektiv. Intressenterna som avses är användarna av finansiella rapporter vilka nämns i IASBs föreställningsram. För att uppnå syftet har tre typfall konstruerats med utgångspunkt i tre olika branscher som förväntas påverkas av den nya intäktsstandarden. Typfallen har därefter analyserats utifrån tillämpning av regelverken RFR 2/IFRS 15 och K3. Metoden som tillämpas i denna studie är av abduktiv karaktär och inom ramen för kvalitativ forskning. Resultatet av studien visar att det förekommer skillnader mellan RFR 2/IFRS 15 och K3. I typfallen uppstår skillnader i tidpunkten och fördelningen vid redovisning av intäkter vilket får effekter på inkomstbeskattning utdelning och nyckeltal. Det är dock svårt att utifrån dessa typfall och faktorer konstatera vilket regelverk som är mer fördelaktigt ur ett intressentperspektiv. När hänsyn tas till att RFR 2/IFRS 15 är mer omfattande och detaljrik än K3 kan däremot RFR 2/IFRS 15 anses vara det regelverk som är mer gynnsamt för intressenterna av den anledningen att det förser intressenterna med mer användbar och utförlig information. / Revenue recognition is an essential part of accounting theory and is used for determining financial performance. It is also a meaningful measure for stakeholders that use revenue recognition to estimate companies’ financial performance. In 2002 the IASB started a project to develop a new international revenue recognition standard. The reason for this was to increase the comparability across companies and countries as well as develop a more consistent framework for revenue recognition. Unlisted Swedish companies which classifies as larger companies should apply the Swedish regulation K3, but they also have the opportunity to practise the international IFRS regulation by applying the Swedish recommendation RFR 2. The purpose of this study is to examine possible differences that may arise between the revenue recognition of RFR 2/IFRS 15 and K3 regarding income tax, dividends and financial ratios. The study will also show which regulation is most beneficial from a stakeholder perspective. The stakeholders referred to are the users of the financial statements in IASB’s conceptual framework. In order to achieve the purpose of this study, three hypothetical examples have been designed based on three different industries that are expected to be the most affected of the new revenue recognition standard. The hypothetical examples have then been analyzed based on the application of RFR 2/IFRS 15 and K3. The method for this study is an abductive character and within the frames of qualitative research. The findings of this study indicate that differences appear between RFR 2/IFRS 15 and K3. The hypothetical examples show that differences occur in the timing and allocation of revenue recognition which have an effect on income tax, dividends and financial ratios. Even though differences occur it is difficult to conclude which regulation is the most beneficial from a stakeholder perspective, based on these hypothetical examples and elements. However, considering RFR 2/IFRS 15 being more comprehensive and detailed than K3, RFR 2/IFRS 15 may be considered more beneficial to stakeholders as it provides stakeholders with more useful and extensive information.

nÃo hà / Esta pesquisa objetiva o desenvolvimento de um modelo de risco para instituiÃÃes bancÃrias, fundamentado em Ãndices financeiros, com a aplicaÃÃo de conceitos de matrizes de migraÃÃo de ratings. Para isso, sÃo utilizados dados contÃbeis pÃblicos destas entidades, que recebem o acompanhamento de autoridades monetÃrias, devido ao risco sistÃmico que podem representar, e das matrizes de migraÃÃo de rating, que tÃm se tornado de grande utilidade na teoria moderna de administraÃÃo do risco. Assim, em uma abordagem teÃrica e experimental, foi gerado um modelo, com a utilizaÃÃo de matrizes de migraÃÃo, construÃdas a partir de classificaÃÃes de risco baseadas em Ãndices financeiros. Foram utilizados demonstrativos financeiros semestrais e anuais de 79 instituiÃÃes bancÃrias, no perÃodo de 2001 a 2009. Verificou-se que as matrizes de migraÃÃo que mais se aproximavam de matrizes de rating foram aquelas com menores nÃmeros de classes de risco e de maiores intervalos. Quanto aos Ãndices da equaÃÃo do modelo, verificou-se que a alavancagem e a relaÃÃo capital/depositantes foram os que apresentaram maiores ponderaÃÃes. Quando as notas estimadas foram comparadas com as notas das agÃncias Austin e Fitch, observou-se baixo nÃmero de notas iguais, porÃm em quantidade significativa, quando consideradas tambÃm as notas iguais e as que diferiam em apenas um nÃvel de risco. / This research aims to develop a risk model for banks, based on financial indices, with the application of concepts of migration matrices ratings. For this, public accounting data are used these entities that receive the monitoring of monetary authorities, due to the systemic risk that may represent, and rating migration matrices, which have become very useful in the modern theory of risk management. Thus, in a theoretical and experimental, a model was created with the use of migration matrices, constructed from risk scores based on financial indices. We used half-yearly and annual financial statements of 79 banks in the period 2001 to 2009. It was found that the matrix of migration that were closest to the rating matrices were those with smaller numbers of classes of risk and greater intervals. Regarding the indexes of the model equation, it was found that the leverage ratio and capital / depositors were those with higher weightings. When notes were compared with the estimated scores of agencies Fitch and Austin, we found low numbers of equal notes, but in significant amounts when the notes considered equal and the only one that differed in level of risk.