The dissertation deals with credit risk and default prediction for software companies in the light of Basel II, the new capital accord for financial institutions. A credit risk model was developed which can be used by lenders to predict the default of software companies. Such model was developed by using three independent approaches: In a first approach, a model was created which was based solely on quantitative data (i.e. accounting data). In a second approach, a model was developed which was based entirely on qualitative information, including management skills, know how, quality of services and others. In a third approach, the quantitative and the qualitative models were combined. The results indicate that a credit risk model which is based on both quantitative and qualitative information yields the strongest predictive power. (author´s abstract)

Master of Science / Department of Agricultural Economics / Elizabeth Yeager / The main objective of this analysis was to examine the profitability and efficiency of Kansas farms in order to draw inferences among the profitability, efficiency, and growth of agricultural producers in Kansas. The time period analyzed was 2005 to 2015. Farms in the sample include a mix of 564 crop and/or livestock operations with 11 years of continuous data through the Kansas Farm Management Association data-bank. Efficiency scores were calculated to determine how close each farm was to the production possibilities frontier, or their cost efficiency. Profitability measures, (operating profit margin and return on assets), were obtained for each farm. The profitability dynamics in 2014 and 2015 for these farms changed compared to previous years. Crop farms generated less profits in 2014 and 2015 compared to previous years, and relative profits from average fluctuated more for sampled farms in 2014 and 2015. Farms were also categorized into risk classes. These classifications aim at distinguishing farms that are profitable or not, and their level of solvency, utilizing their net farm income from operations and their debt to asset ratio. Farms are migrating from the low risk classification, showing that Kansas farms are becoming less profitable, but are not transitioning to a higher risk solvency state. These farms will need to focus on utilizing their inputs more efficiently to keep their solvency levels in check. After analyzing persistence in profitability, the results suggest that farms with higher return on assets tend to be more solvent, but farms with higher operating profit margin tend to be less solvent. The analysis also suggests that there might have been persistence in profits in the years prior to 2015. The analysis of relative positioning of farms in terms of return on assets suggests that during 2007-2011 some farms were able to consistently differentiate themselves by generating either below or above normal profits. Some farms were able to become more profitable in 2012 and 2013, while others lagged behind supported by regression results that signaled divergence of profitability levels. The relative positioning analysis for operating profit margin indicates that farms had similar operating profit margins from 2010 through 2014, and divergence occurred in 2015 by farms that were able to differentiate themselves more through the average operating profit margin. Next the efficiencies of the farms were examined. Analysis of the efficiency scores suggests that the cost efficiencies of Kansas farms are not explained by risk classification significantly, but the crop-labor percentage ratio significantly explains the cost efficiency of the farms. The relationship between cost efficiency and profitability measures proved to be the strongest out of the three performance measures due to their correlation. The final step in the analysis was to examine farm characteristics of the top performing farms. Farms were ranked by profitability measurements and the efficiency measure. Variables of interest that were significantly different between the top 25 percent and the bottom 25 percent of farms include total farm assets, value of farm production, crop-labor percentage, crop acres, number of workers, and age of operators.

This master´s thesis applies to identifying and rating risks connected to competitiveness of Kellys bicycles company that operates in the area of constructing and selling bicycles. Theoretical basis consists of scientific knowledge from marketing, market, risk analysis and rating. Analytical part consists of company introduction, analysation of company´s external environment and analysation of activities related with marketing. Last part of this thesis is focused on offers in minimasing risks of company´s activities.

We assume pairs of random variables (X_i, Y_i), whereby the real variable X_i measures the creditworthiness of individual i with i = 1, . . . , n. The Bernoulli variable Y_i represents the default indicator of individual i. Our main target is a division of the creditworthiness into a given number of groups with a homogeneous default risk, i.e. to estimate rating classes. The framework of change point analysis provides a nonparametric method to estimate the breakpoints between the rating classes under quite weak assumptions. Up to now, the theory of breakpoint estimation is developed under the assumption of exactly one breakpoint. The contribution at hand, basically implements this theory, but extends it into a multi-stage heuristic. That means, we sequentially apply the theory for only one breakpoint as a multi-stage procedure. With this article we transfer the interesting theoretical issue of breakpoint estimation into an applicable form. Thereby, all the results are checked and obtained by simulation. The main results are as follows. Applying a sequential breakpoint estimation basically works and leads to outcomes of practical purpose. Thereby, the multistage heuristic reveals some weakness esp. in the case of quite huge differences between default probabilities that can be resolved by some interventions.

[pt] O presente estudo tem por objetivo construir um modelo que permita a categorização dos fatores que geram o conceito de Risco Soberano e que defina as variáveis que compõem cada um deles. Para isso, usam-se os métodos estatísticos conhecidos como Análise Fatorial e Análise dos Componentes Principais. Apresenta-se como resultado do trabalho um modelo que é simultaneamente conciso - pelo pequeno número de variáveis que o compõem, em contraposição ao número elevado citado na literatura sobre o tema - e eficiente - uma vez que ele permite montar um Índice de Risco Soberano compatível com os ratings das principais agências internacionais e com os retornos de títulos soberanos. Utilizou-se o Coeficiente de Correlação de Postos de Spearman para proceder a comparação entre a ordenação de países pelo índice proposto e as ordenações derivadas dos ratings e dos retornos dos títulos. / [en] This study is designed to build a model which enables the categorization of factors that not only originates the concept of Sovereign Risk but also defines the variables that compound each factor. To fulfill such an objective, statistical methods known as Factor Analysis and Principal Component Analysis are employed. As result of this work, a model is presented that is simultaneously concise - given its small number of variables, in contrast to the large number of variables mentioned on the literature about this theme - and efficient - since it permits the creation of a Sovereign Risk Index that is compatible both with ratings of the major international agencies and with sovereign bond yields. In order to compare the countries ranking based on the Index to the rankings derived from ratings and bond yields, Spearman`s Ranking Correlation Coefficient is used. / [es] EL presente estudio tiene como objetivo construir un modelo que permita la categorización de los factores que generan el concepto de Riesgo Soberano y que defina las variables que lo componen. Para eso, se utilizan conocidos métodos estadísticos como Análisis Factorial y Análisis de Componentes Principales. Como resultado del trabajo se presenta un modelo que es simultáneamente conciso - por el pequeño número de variables que lo componen, en contraposición con el elevado número que es citado en la literatura sobre el tema - y eficiente - una vez que permite montar un Índice de Riesgo Soberano compatíble con los ratings de las principales agencias internacionales y con los retornos de títulos soberanos. Se utilizó el Coeficiente de Correlación de Spearman para comparar el orden de países por el índice propuesto y el orden derivado de los ratings y de los retornos de los títulos.

[pt] O papel deste estudo foi investigar se as alterações de ratings de países da América Latina produzem impactos significativos no mercado acionário brasileiro. Por ser tratar de teste de hipótese semiforte de eficiência de mercado, o estudo foi conduzido através de teste estatístico paramétrico. Os resultados encontrados corroboram com hipótese de efeito contágio no mercado acionário brasileiro, através do índice IBX. O estudo também conclui que a intensidade do impacto também depende do tipo de informação incorporada nos anúncios de mudanças de classificações soberanas. / [en] The objective of this study was to investigate if sovereign rating changes for Latin America affect the Brazilian stock market. To measure this potential impact, the parametrical statistical test of event study was adopted, commonly used in semi-strong market efficiency tests. The results support the idea of contagion effects in the Brazilian Market through the IBX index. This study also concludes that the impact depends on the type of announcement of ratings changes.

<p><strong>Abstract </strong></p><p><strong>Purpose </strong>The purpose of this study is to investigate the methods used for valuating private limited knowledge based companies and if a new approach is required, create or modify a foundation that will constitute as a base within the valuation process.</p><p><strong>Method </strong>This is a qualitative study using interviews to obtain primary data. People working in the valuation industry were contacted and we got eight respondents. The questions were designed to answer our purpose and research questions. Telephone interviews were chosen due to the fact that we believed the response would be higher.      <strong></strong></p><p><strong> </strong></p><p><strong>Frame of References </strong>The theories used in this section is divided into three parts; the financial analysis including traditional valuating methods such as the Discounted Cash Flow model and relative valuating and multiples. The non-financial analysis focus on the underlying analysis consistent of structural- and intellectual capital and also value drivers that are creating value for the firm. In the end other theories concerning the analysis are presented, such as the risk-return trade-off, risk rating systems and analytical hierarchy process.            <strong> </strong></p><p><strong> </strong></p><p><strong>Empirical Findings </strong>In this section the presentations of the respondents’ answers and</p><p><strong>and Analysis </strong>a brief analysis related to each question. After this an extended analysis is presented focusing on the subject and our risk scheme and guidelines we created/modified. The extended analysis is connected to the respondents’ answers. The purpose of this section is to have a better understanding about the risk of transient intellectual capital and give recommendations how to handle it. Also, guidelines of how to weight different value driver are discussed.</p><p><strong>Conclusion </strong>We concluded that all valuations utilize more than one approach in order to estimate the most accurate value for the company. For knowledge based companies the biggest risk with a M&A transaction is the probability of diminishing the intellectual capital. We constructed a model that will manage this risk based on our interviews and established theories.</p><p> </p>

Abstract Purpose The purpose of this study is to investigate the methods used for valuating private limited knowledge based companies and if a new approach is required, create or modify a foundation that will constitute as a base within the valuation process. Method This is a qualitative study using interviews to obtain primary data. People working in the valuation industry were contacted and we got eight respondents. The questions were designed to answer our purpose and research questions. Telephone interviews were chosen due to the fact that we believed the response would be higher.      Frame of References The theories used in this section is divided into three parts; the financial analysis including traditional valuating methods such as the Discounted Cash Flow model and relative valuating and multiples. The non-financial analysis focus on the underlying analysis consistent of structural- and intellectual capital and also value drivers that are creating value for the firm. In the end other theories concerning the analysis are presented, such as the risk-return trade-off, risk rating systems and analytical hierarchy process.             Empirical Findings In this section the presentations of the respondents’ answers and and Analysis a brief analysis related to each question. After this an extended analysis is presented focusing on the subject and our risk scheme and guidelines we created/modified. The extended analysis is connected to the respondents’ answers. The purpose of this section is to have a better understanding about the risk of transient intellectual capital and give recommendations how to handle it. Also, guidelines of how to weight different value driver are discussed. Conclusion We concluded that all valuations utilize more than one approach in order to estimate the most accurate value for the company. For knowledge based companies the biggest risk with a M&amp;A transaction is the probability of diminishing the intellectual capital. We constructed a model that will manage this risk based on our interviews and established theories.

[pt] A crescente integração econômica e financeira mundial vem continuamente intensificando a demanda por informações visando subsidiar a tomada de decisões de um investidor global, geralmente baseada em dois fatores primordiais: risco e retorno. Nesse contexto, tornam-se extremamente interessantes as informações produzidas pelas agências de classificação de risco. Tais agências representam, através de notas, o risco de uma determinada nação não arcar com suas dívidas. Conseqüentemente, ao classificar o risco soberano de um país, influenciam investidores de todo o mundo, impactando principalmente, os mercados emergentes, como o brasileiro. Assim, o objetivo deste trabalho é avaliar os efeitos de mudanças dos ratings soberanos brasileiros atribuídos pelas agências de classificação de risco, no mercado acionário nacional. É percorrido um histórico das agências de rating e dos principais bonds por elas avaliados. Também é fornecida uma detalhada descrição das características daquelas agências e a forma de que elas influenciariam o mercado de capitais. Em seguida, através de testes estatísticos, desenvolve-se um estudo de evento, para analisar os efeitos verificados sobre os retornos do índice BOVESPA, nos períodos de upgrade, downgrade ou reavaliação assinalados pelas agências.Por fim, resultados serão expostos e as conclusões apresentadas. / [en] The growing economic and financial integration of the world is continuously intensifying the demand for information, in order to subsidize the decision making of the global investor, generally based on two major factors: risk and return. In this context, the data produced by the Credit Risk Agencies becomes extremely interesting. Such Agencies represent, with grades, the risk of a specific nation does not pay its debt. Consequently, when there is a Sovereign Risk classification of a country, these companies influence investors all over the world, impacting mostly the emerging markets, as well as the Brazilian market. Therefore, the objective of this work is to evaluate the effects of Brazilian Sovereign ratings, attributed by the Credit Agencies, in the national stock bond markets. A history of the Credit Agencies and the most important bonds evaluated by them will be reviewed. Furthermore, a detailed description of the characteristics of those agencies and how they influence the capital markets will be provided. Following, through statistical tests, an event study will be developed to analyze the effects verified in the returns of BOVESPA index, in events of upgrade, downgrade and outlook revision signed by the Credit Agencies. Finally, results are provided and conclusions presented.

Die Arbeit ANLEIHERATING UND BONITÄTSRISIKO untersucht die Zusammenhänge zwischen dem Rating von Anleihen, dem Risiko dieser Anleihen sowie ihren Risikoprämien (Spreads). Dazu wird in einem ersten Schritt - auf analytischer Ebene - untersucht, wie Ratings vergeben werden und welchen Einschränkungen sie unterliegen. Die wichtigsten Einschränkungen für den Kapitalmarkt hinsichtlich der Ableitung von quantitativen Risikogrößen (Ausfallwahrscheinlichkeit und ggf. Ausfallschwere) sind: Ordinalität und Relativität der verwendeten Skalen; die Zeitverzögerungen bei Ratingänderungen; die Intransparenz, Subjektivität und Urteilsunabhängigkeit des Ratingverfahrens bzw. der Ratingagenturen; die Erstellung von auftragslosen Ratings; die mangelnde Vergleichbarkeit von Ratings (zeitlich, zwischen Emissionen und zwischen Agenturen); die fehlende Äquidistanz von Ratings; das Risiko fehlerhafter Ratings. In einem zweiten Schritt wird empirisch untersucht, in welcher Höhe vom Markt Spreads (Überrenditen gegenüber den als risikolos geltenden Bundesanleihen) - je nach Rating - für bestimmte Anleihen gefordert werden. Datenbasis sind Kupon-Anleihen (ohne Sonderrechte) des DM-Euromarktes mit täglichen Kursen im Zeitraum Januar 1990 bis Dezember 1995. Die Untersuchungen bestätigen die Relativität: Ratings definieren nur im langfristigen Durchschnitt die Renditeabstände zwischen den verschiedenen Klassen. Kurzfristige Veränderungen der Spreads hingegen hängen von Veränderungen des allgemeinen Zinsniveaus und dem Verlauf der Zinsstrukturkurve ab. Diese beiden Größen weisen dabei einen negativen Einfluß auf, d.h. Zinserhöhungen führen zu Verringerungen der Spreads. Grundsätzlich gilt dabei aber, dass diese Effekte umso stärker ausfallen, je geringer die Bonität der Anleihen ist. Zusätzlich hängen die Spreadänderungen auch (positiv) von Veränderungen der Spreads der jeweils anderen Klassen ab. Als mögliche Erklärungsansätze bieten sich für diese Beobachtung auch an, dass der Markt Schwankungen der erwarteten Ausfallwahrscheinlichkeiten antizipiert und/oder Veränderungen der allgemeinen Risikoeinstellung vorliegen.