939 resultados para Financial analysis


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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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Dissertação para obtenção do Grau de Doutor em Alterações Climáticas e Políticas de Desenvolvimento Sustentável

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Chagas disease was an important medical and social problem in almost all of Latin America throughout the twentieth century. It has been combated over a broad swath of this continent over recent decades, with very satisfactory results in terms of vector and transfusional transmission. Today, a surveillance stage still remains to be consolidated, in parallel with appropriate care required for some millions of infected individuals who are today living in endemic and non-endemic areas. Contradictorily, the good results attained have generated excessive optimism and even disregard among health authorities, in relation to this disease and its control. The loss of visibility and priority may be a logical consequence, particularly in Latin American healthcare systems that are still disorganized and overburdened due to insufficiencies of financial and human resources. Consolidation of the victories against Chagas disease is attainable but depends on political will and continual attention from the most consequential protagonists in this struggle, especially the Latin American scientific community.

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The goal of this thesis is the study of a tool that can help analysts in finding sequential patterns. This tool will have a focus on financial markets. A study will be made on how new and relevant knowledge can be mined from real life information, potentially giving investors, market analysts, and economists new basis to make informed decisions. The Ramex Forum algorithm will be used as a basis for the tool, due to its ability to find sequential patterns in financial data. So that it further adapts to the needs of the thesis, a study of relevant improvements to the algorithm will be made. Another important aspect of this algorithm is the way that it displays the patterns found, even with good results it is difficult to find relevant patterns among all the studied samples without a proper result visualization component. As such, different combinations of parameterizations and ways to visualize data will be evaluated and their influence in the analysis of those patterns will be discussed. In order to properly evaluate the utility of this tool, case studies will be performed as a final test. Real information will be used to produce results and those will be evaluated in regards to their accuracy, interest, and relevance.

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This study analyses financial data using the result characterization of a self-organized neural network model. The goal was prototyping a tool that may help an economist or a market analyst to analyse stock market series. To reach this goal, the tool shows economic dependencies and statistics measures over stock market series. The neural network SOM (self-organizing maps) model was used to ex-tract behavioural patterns of the data analysed. Based on this model, it was de-veloped an application to analyse financial data. This application uses a portfo-lio of correlated markets or inverse-correlated markets as input. After the anal-ysis with SOM, the result is represented by micro clusters that are organized by its behaviour tendency. During the study appeared the need of a better analysis for SOM algo-rithm results. This problem was solved with a cluster solution technique, which groups the micro clusters from SOM U-Matrix analyses. The study showed that the correlation and inverse-correlation markets projects multiple clusters of data. These clusters represent multiple trend states that may be useful for technical professionals.

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This paper analyses, through a dynamic panel data model, the impact of the Financial and the European Debt crisis on the equity returns of the banking system. The model is also extended to specifically investigate the impact on countries who received rescue packages. The sample under analysis considers eleven countries from January 2006 to June 2013. The main conclusion is that there was in fact a structural change in banks’ excess returns due to the outbreak of the European Debt Crisis, when stock markets were still recovering from the Financial Crisis of 2008.

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The purpose of this paper is to conduct a methodical drawback analysis of a financial supplier risk management approach which is currently implemented in the automotive industry. Based on identified methodical flaws, the risk assessment model is further developed by introducing a malus system which incorporates hidden risks into the model and by revising the derivation of the most central risk measure in the current model. Both methodical changes lead to significant enhancements in terms of risk assessment accuracy, supplier identification and workload efficiency.

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Corporate social responsibility (CSR) literature has largely neglected consumers’ perceptions in the debate regarding the role of CSR in the aftermath of the financial crisis. In that context, this study aims to test the possibility that consumers’ perceptions of CSR level, firm reputation and brand trust, might depend on the type of industry sector of a firm, the level of fit of an initiative or both. By conducting a survey on Portuguese consumers and running a two-way analysis of variance, it suggests that solely the type of industry sector has an effect on consumer perception and that consumers are less tolerable of controversial industries.

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In this discussion OLS regressions are used to study the factors that influence sovereign yield spreads and domestic bank indeces for a set of euro area countries. The results show that common factors explain changes in bank indeces better than in the yields. Moreover, although there is some country differentiation, a common pattern among all is visible. A contemporary spillover effect between banks and sovereigns emerged after bank bailouts and became stronger with the burst of the sovereign debt crisis. The vicious cycle between the two has contributed to the escalation of spreads and to painful austerity measures.

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Marginal Expected Shortfall (MES) is an approach used to measure the systemic risk financial institutions face. It estimates how significantly systemic events (poor market performance, out of 1.6 times Standard Deviation borders) are expected to affect market capitalization of a particular firm. The concept was developed in the late 2000s and is widely used for cross-country comparisons of financial firms. For the purposes of generalization of this technique it is often used with market data containing non-domestic currencies for some financial firms. That may lead to results having currency noise in them as it is shown for 77 UK financial firms in our analysis between 2001 and 2014.

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Companies in the Extractive Industry (E.I) have some particularities and special regulation that provides an interesting study of inventory and reporting in their financial statements. The theme thus chosen here, aims to make a comparison of the various methods of reporting inventories (recognition, measurement, presentation and disclosures) as well as the different accounting regulations in place. Moreover, inventories are a current asset which represents a large per cent of total assets. Another is that it also provides an opportunity for analysis of the different regulations in place for disclosures; the different standards implemented- IAS, US GAAP and/or regional standards.

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The paper studies the relationship between four differently rated bank’s financial profile and their standalone credit rating issued by Moody’s. The comparative analysis shows an example that despite their pricing power and geographical coverage, larger banks do not necessarily have better credit ratings. Instead, business model and risk appetite seem to be the defining factors of banks’ vulnerability to shocks, such as the Spanish real estate crisis. The risk-return relationship is also identified in the banks’ fundamentals meaning that while expansionary strategy in riskier asset classes enhances margins, it also potentially distorts the credit risk profile.

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The Financial Leverage of Large Portuguese Firms in the European Context This paper studies the leverage, cost of debt servicing ability and structure of debt maturity of large Portuguese firms, over the pre-crisis (2006-2009) and post-crisis (2010-2013) periods through a comparative analysis with other European peers. We document that large Portuguese firms have been reducing their leverage since the end of 2009. We find that this decrease in leverage is not a consequence higher Equity levels but rather a result of asset’s downsizing. We also document that Portuguese firms are still more leveraged than their European peers, even though this difference has decreased over time. High corporate debt levels are transversal across industries.

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In this study, the metabolomics characterization focusing on the carotenoid composition of ten cassava (Manihot esculenta) genotypes cultivated in southern Brazil by UV-visible scanning spectrophotometry and reverse phase-high performance liquid chromatography was performed. Cassava roots rich in -carotene are an important staple food for populations with risk of vitamin A deficiency. Cassava genotypes with high pro-vitamin A activity have been identified as a strategy to reduce the prevalence of deficiency of this vitamin. The data set was used for the construction of a descriptive model by chemometric analysis. The genotypes of yellow-fleshed roots were clustered by the higher concentrations of cis--carotene and lutein. Inversely, cream-fleshed roots genotypes were grouped precisely due to their lower concentrations of these pigments, as samples rich in lycopene (redfleshed) differed among the studied genotypes. The analytical approach (UV-Vis, HPLC, and chemometrics) used showed to be efficient for understanding the chemodiversity of cassava genotypes, allowing to classify them according to important features for human health and nutrition.