The theoretical part of this master thesis deals with creation and solution of financial distress and analysing classification models. In the practical part I defined own methods for financial distress prediction of company using discriminant analysis and logistic regression.

Um dos temas mais estudados na área de finanças, em especial na análise de créditos, são os modelos que buscam prever a capacidade das empresas em se manterem solventes. Via de regra, tais estudos buscam, dentre vários indicadores, aqueles que se mostram mais apropriados para realizar tal predição. Nesse trabalho propõe-se um outro olhar sobre os modelos de previsão. Partindo de modelos já consagrados na literatura, escolheram-se os indicadores contábeis mais utilizados, que foram comparados, através da Análise Discriminante e da Regressão Logística, com os indicadores oriundos do Modelo Dinâmico. O objetivo do estudo foi verificar se os indicadores do Modelo Dinâmico oferecem melhores resultados que os indicadores tradicionais. O trabalho se baseia numa amostra com 48 empresas, composta de 24 insolventes e as outras 24 ditas como saudáveis, tratadas como pares das insolventes, escolhidas dentro do mesmo setor econômico de cada uma das insolventes. Além disso, foi incluída no estudo a classificação de empresas de Fleuriet como variável qualitativa. Os resultados obtidos não apresentam evidências sobre a superioridade de um ou outro conjunto de indicadores, mas, os melhores resultados alcançados derivam da inclusão da classificação de empresas de Fleuriet, seja através da Análise Discriminante, seja através da Regressão Logística, conseguindo no melhor dos resultados, um percentual de acerto total de 83,3%. A análise minuciosa dos erros de classificação ensejou uma proposta de reordenação dos tipos de situação de liquidez originalmente propostos por Fleuriet. / One of the most studied topics in finance, particularly in credit analysis, are the models that seek to predict the ability of firms to remain solvent. Usually, such studies among various indicators, seek those who are most appropriate to perform such a prediction. In this work we propose a different view of the forecast models. Starting from models already established in the literature, were chosen the most used financial indicators, which were compared by discriminant analysis and logistic regression, with indicators derived from the Dynamic Model. The aim of the study was to determine whether the indicators of Dynamic Model offer better results than the traditional indicators. The work is based on a sample of 48 companies, consisting of 24 insolvent 24 and the other said to be healthy treated as pairs of insolvent chosen within the same economic sector of each insolvent. Furthermore, it was included in the study the classification of companies as Fleuriet qualitative variable. The results show no evidence of the superiority of one or another set of indicators, but the best results achieved derive from the inclusion of classification Fleuriet companies, either through discriminant analysis, logistic regression is through, achieving the best results a percentage of the total adjustment of 83.3 %. A thorough analysis of the classification errors gave rise a proposed reorganization of the types of liquidity situation originally proposed by Fleuriet.

Background: As high HIV transmission rates persist in Sub-Saharan Africa, the effect of wealth inequality rather than solely absolute wealth as a potential driver of the HIV epidemic has been given increased attention in recent research, but has not yet been investigated in the Nigerian setting. As, particularly in contexts of socioeconomic inequality, individuals may face barriers to both obtaining health-related knowledge and translating this knowledge into actual engagement in preventive measures, it is relevant to assess the level of HIV-related knowledge in the Nigerian population. Furthermore, it is of interest to investigate its socioeconomic predictors, and to identify risk-groups for low HIV-related knowledge, which consequentially are also potential risk groups for high HIV transmission. This will ultimately facilitate the targeting and implementation of more appropriate and effective preventive interventions among these groups. Due to the country’s high HIV prevalence and its ethnic and socioeconomic heterogeneity, it is both an interesting and highly relevant setting in which to analyse the socioeconomic determinants of HIV-related knowledge. Methods: Utilizing data from the Nigerian Demographic and Health Survey, Paper 1 of this thesis investigates wealth inequality as a predictor of low HIV-related knowledge in the Nigerian population through logistic regression modeling. The effects of other sociodemographic factors such as sex, literacy and rural or urban residence on HIV-related knowledge are also explored. In paper 2, a trend analysis is conducted of HIV-related knowledge in the country from 2003 to 2013, with changes in these trends represented graphically, stratified by various sociodemographic factors. ARIMA models were fit to the 2003-2013 trend data. Finally, Paper 3 presents a systematic review (using the Medline and Embase databases) and meta-analysis (conducted in R) of HIV-related knowledge interventions in Sub-Saharan Africa or among the African Diaspora, synthesising the available evidence for the efficacy of such interventions in 1) improving HIV-related knowledge, 2) resulting in increased engagement in preventive measures and safe sexual practices, and 3) reducing HIV incidence. Random-effects models were used for the meta- analyses. Results: The logistic regression model indicated that females were more than twice as likely as males to have low HIV-related knowledge in each wealth inequality category. In addition, females were more likely to have correct knowledge of mother-to-child transmission than males, but were over 1.5 times more likely to have poor knowledge of HIV risk reduction measures. Individuals with lower literacy levels were almost twice as likely as literate respondents to have low HIV-related knowledge. Ethnicity, religious affiliation, relationship status, and residing in rural areas were additional significant predictors of HIV-related knowledge. The trend analysis indicated an overall increase in HIV-related knowledge between 2003 and 2013, but a decrease in knowledge of mother-to-child-transmission. In addition, State-level disparities in knowledge regarding HIV risk reduction increased over time. The meta-analysis of HIV education interventions demonstrated significantly higher odds of correct knowledge of transmission routes as well as condom use, but insignificantly lower odds of HIV incidence. Conclusions: HIV-related knowledge in this sample is generally low among females, those with low literacy levels, the poor, the unemployed, those residing in rural areas, those with traditional religious beliefs, and those living in states with the highest wealth inequality ratios. The meta-analysis of HIV-related knowledge interventions in Paper 3 indicates that such interventions are generally effective at improving not only HIV-related knowledge but also increasing condom use, and should thus be targeted at the risk groups identified in Papers 1 and 2, in order to work towards the reduction of HIV transmission.

Made available in DSpace on 2016-03-07T19:20:25Z (GMT). No. of bitstreams: 0 Previous issue date: 2015-12-04. Added 1 bitstream(s) on 2016-03-07T19:23:55Z : No. of bitstreams: 1 000858681.pdf: 948139 bytes, checksum: 66d2f552c3444ea49441913b2f43d171 (MD5) / A gestão de cadeias de suprimentos (GCS) requer, dentre diversos aspectos, a integração de processos de negócios chaves ao longo de toda a cadeia. A literatura acadêmica tem contribuído para o aprimoramento e entendimento dessas práticas, para que funcionem adequadamente em diversos setores da indústria nacional. No entanto, poucos são os estudos referentes à utilização da GCS no setor calçadista brasileiro, o qual tem uma expressiva relevância para economia nacional. Esse trabalho teve como objetivo identificar as principais práticas de GCS que são adotadas atualmente pelo setor calçadista da cidade de Jaú - SP. O método escolhido para o trabalho foi o de estudo de casos múltiplos, sendo investigadas três cadeias de suprimentos, compostas por três elos cada. Os resultados da pesquisa mostram a ausência de práticas colaborativas, de integração e de planejamento conjunto apoiadas por modernas ferramentas de TIC nas cadeias estudadas, além de um elevado grau de conhecimento de tais práticas pelos entrevistados / The supply chain management (SCM) requires, among many things, the integration of key business processes throughout the chain, being effective to manage the competitive challenges facing compannies. The academic literature has contributed to the improvement and understanding of these practices, to function properly in various sectors of national industry. However, there are few studies on the use of GCS in the Brazilian footwear indutry, which has a significant importance for the national economy. This study aimed to identify key practices that GCS are currently adopted by the footwear industry in the city of Jaú-SP. The method chosen for the work the study of multiple cases being investigated three supply-chains, each composed of three links. The survey results show the absence of collaborative practices, integration and assembly supported by modern planning ICT tools in the studied chains, as well as a high degree of ignorance of such practices by respondents

Made available in DSpace on 2016-06-02T20:06:12Z (GMT). No. of bitstreams: 1 DissJBB.pdf: 632747 bytes, checksum: 7f6e8caa78736a965ecb167ee27b7cc3 (MD5) Previous issue date: 2006-04-18 / Universidade Federal de Sao Carlos / This work consider the problem of how to incorporate model selection uncertainty into statistical inference, through model averaging, applied to logistic regression. It will be used the approach of Buckland et. al. (1997), that proposed an weighed estimator to a parameter common to all models in study, where the weights are obtained by information criteria or bootstrap method. Also will be applied bayesian model averaging as shown by Hoeting et. al. (1999), where posterior probability is an average of the posterior distributions under each of the models considered, weighted by their posterior model probability. The aim of this work is to study the behavior of the weighed estimator, both, in the classic approach and in the bayesian, in situations that consider the use of binary logistic regression, with foccus in prediction. The known model-choice selection method Stepwise will be considered as form of comparison of the predictive performance in relation to model averaging. / Esta dissertação considera o problema de incorporação da incerteza devido à escolha do modelo na inferência estatística, segundo a abordagem de ponderação de modelos, com aplicação em regressão logística. Será utilizada a abordagem de Buckland et. al. (1997), que propuseram um estimador ponderado para um parâmetro comum a todos os modelos em estudo, sendo que, os pesos desta ponderação são obtidos a partir do uso de critérios de informação ou do método bootstrap. Também será aplicada a ponderação bayesiana de modelos como apresentada por Hoeting et. al. (1999), onde a distribuição a posteriori do parâmetro de interesse é uma média da distribuição a posteriori do parâmetro sob cada modelo em consideração ponderado por suas respectivas probabilidades a posteriori. O objetivo deste trabalho é estudar o comportamento do estimador ponderado, tanto na abordagem clássica como na bayesiana, em situações que consideram o uso de regressão logística binária, com enfoque na estimação da predição. O método de seleção de modelos Stepwise será considerado como forma de comparação da capacidade preditiva em relação ao método de ponderação de modelos.

Made available in DSpace on 2014-12-02T11:16:53Z (GMT). No. of bitstreams: 0 Previous issue date: 2014-06-25Bitstream added on 2014-12-02T11:21:14Z : No. of bitstreams: 1 000792585.pdf: 8584128 bytes, checksum: c42d6cc0156d1406200b78200a89d4e6 (MD5) / O objetivo da tese é elaborar um construto teórico de mitigação do efeito chicote considerando a confiança e a colaboração no gerenciamento da cadeia de suprimentos. Para tanto, realiza-se uma pesquisa qualitativa com base na revisão sistemática da literatura em que o construto é testado por meio de um estudo de caso, envolvendo empresas da área médico-hospitalar pertencentes a uma mesma cadeia de suprimentos... (Resumo completo, clicar acesso eletrônico abaixo) / Tha aim of the thesis is to develop a theorical construct about mitigation of the bullwhip effect, considering trust and collaboration in managing the supply chain. The study presents a qualitative research based on systematic literature review, which is tested through field research, involving companies in the medical and hospital area belonging to the same supply chain ... (Complete abstract click electronic access below)

Este trabalho apresenta uma metodologia para avaliação da satisfação de clientes em uma cadeia logística, que visa buscar a melhoria dos serviços logísticos. A metodologia utiliza técnicas estatísticas, técnicas de pesquisa de mercado e técnica de análise de decisão. A técnica de análise de decisão utilizada nesta metodologia é o Desdobramento da Função Qualidade (QFD) aplicada para planejar melhorias no serviço logístico, priorizando as características do serviço demandadas pelos clientes e os indicadores de desempenho para o mesmo. A aplicação desta metodologia em uma empresa do ramo alimentício resultou na confirmação da metodologia proposta como instrumento de apoio na elaboração de planos de melhorias para sistemas logísticos. / This work introduces a methotology to avaliate the customer’s satisfaction in a logistc chain which objetcs to achieve the logistic services improvement. The proposed methodology apply statistic technics, market researches technics as well as analyses of decision technic. The decision analyses technic used in this methodology is the Quality Function Deployment (QFD) applied to plan a logistic services improvements, giving priority to features of service required by customes and its performance indicator. The employment of this methodology on a food producer company resulted into confirmation of the proposed methodology as a support instrument to the working up of improvement schedules to logistic systems.

abstract: Modern, advanced statistical tools from data mining and machine learning have become commonplace in molecular biology in large part because of the “big data” demands of various kinds of “-omics” (e.g., genomics, transcriptomics, metabolomics, etc.). However, in other fields of biology where empirical data sets are conventionally smaller, more traditional statistical methods of inference are still very effective and widely used. Nevertheless, with the decrease in cost of high-performance computing, these fields are starting to employ simulation models to generate insights into questions that have been elusive in the laboratory and field. Although these computational models allow for exquisite control over large numbers of parameters, they also generate data at a qualitatively different scale than most experts in these fields are accustomed to. Thus, more sophisticated methods from big-data statistics have an opportunity to better facilitate the often-forgotten area of bioinformatics that might be called “in-silicomics”. As a case study, this thesis develops methods for the analysis of large amounts of data generated from a simulated ecosystem designed to understand how mammalian biomechanics interact with environmental complexity to modulate the outcomes of predator–prey interactions. These simulations investigate how other biomechanical parameters relating to the agility of animals in predator–prey pairs are better predictors of pursuit outcomes. Traditional modelling techniques such as forward, backward, and stepwise variable selection are initially used to study these data, but the number of parameters and potentially relevant interaction effects render these methods impractical. Consequently, new modelling techniques such as LASSO regularization are used and compared to the traditional techniques in terms of accuracy and computational complexity. Finally, the splitting rules and instances in the leaves of classification trees provide the basis for future simulation with an economical number of additional runs. In general, this thesis shows the increased utility of these sophisticated statistical techniques with simulated ecological data compared to the approaches traditionally used in these fields. These techniques combined with methods from industrial Design of Experiments will help ecologists extract novel insights from simulations that combine habitat complexity, population structure, and biomechanics. / Dissertation/Thesis / Masters Thesis Industrial Engineering 2018

Despite years of deepening economic integration among the states and regions of the European Union, empirical research remains inconclusive about speed of convergence across regions, if not its existence. This thesis provides novel evidence on convergence in the EU while focusing on development at regional level after the Great Recession. It uses recently developed log t convergence test by Phillips and Sul (2007). Our findings speak against the convergence in level of income per capita among the European regions and give us five clubs of regions converging in their income growth rates instead. Investigating further the geographical distribution of the convergence clubs, we confirm high inequality within the member states and find large continuous area of high convergence clubs in the urbanized part of Western Europe. Furthermore, we investigated the determinants of convergence club membership using Logistic Regression. The main explanatory variable of interest were Business Services (BS), a dynamic sector of the economy with presumably strong positive effect on regional innovative potential. We found positive effect of BS on membership in higher convergence clubs. Yet, this effect seems to diminish for the very highest club.

Capturing mortality became a crucial modelling problem throughout the years due to the raising demand of life insurances and annuities. Fitting three models, namely, logistic, Heligman– Pollard HP4 and power–exponential model, to real life data shows that latter two models represent the actual data quite well. Pricing a term life insurance and a whole life annuity, implemented using the MATLAB software, based on these models ends in the result that the Heligmann–Pollard HP4 model is the less preferable model, in perspective of an insured, than the logistic or power–exponential ones.