Submitted by Filipe dos Santos (fsantos@pucsp.br) on 2017-06-20T12:21:57Z No. of bitstreams: 1 José do Socorro Assis.pdf: 981227 bytes, checksum: 4e2868869711e770d5f230644639437d (MD5) / Made available in DSpace on 2017-06-20T12:21:57Z (GMT). No. of bitstreams: 1 José do Socorro Assis.pdf: 981227 bytes, checksum: 4e2868869711e770d5f230644639437d (MD5) Previous issue date: 2017-06-07 / The key factors when analyzing invested capital returns versus the risks assumed by financial institutions have been widely discussed in corporate finance. The goal of this study is to understand the contribution of economic-financial factors when explaining the risk-adjusted return on capital: RAROC. In this context, this metric, in its starting point, was used on the foundation of capital management in financial institutions under the approaches of risk mitigation versus maximization return. Therefore, this study considers a sample of eleven banks with capital being traded on BM&FBOVESPA and was distributed in three groups: (i) large, (ii) medium and (iii) small size, with the size defined according to the BACEN criteria described in the Financial Stability Report. The analysis of the economic-financial factors are based on the DuPont model, starting from the ROE (Return On Equity), and afterwards, calculating RAROC in financial institutions, considering three factors: i) capital financial leverage, as the ratio between assets allocated to risks and available risk capital; ii) assets profitability, calculated by the ratio between net revenues and risk-weighted assets, and iii) profit margin rate, which measures the operational and tax efficiency based on the ratio of economic profit to net revenues. The period considered in this analysis is from 2010 to 2015 with semiannual data obtained in the Financial Statements and Risk and Capital Management Documents released by financial institutions, which as selected for being the period after the banking crisis of 2008 and 2009. The methodology adopted is empirical-analytic and the type of research that is characterized as quantitative, descriptive and documentary. The results obtained with the use of Pearson (r) statistical correlation techniques and multiple linear regression in the stepwise method (r2 adjusted), as well as the hypothesis tests, indicated the existence of peculiar characteristics to the studied groups. The group of large banks presented the profit margin rate as the one with the highest explanatory capacity of RAROC with a correlation of 0.982 and r2 of 96.3%, thus demonstrating that the efficient management of the structure costs was presented as a differentiating factor in the Risk-adjusted return on capital. Regarding the group of medium-sized banks, the factors of profitability and profit margin rate profitability presented a modest explanatory capacity and quite similar with r2 of 48.4% and 43.1%, respectively. In the group of small banks, the profit margin rate had a high explanatory power with r2 of 76.1%. It should be considered that the market of medium and small banks is more vulnerable to economic crises and presents a higher cost of funding, thus requiring a continuous search for high specialization, differentiation and flexibility in their businesses. The justification for this work is based on the relevance and timeliness of the theme for the academic community and the representativeness of banking activity in the country's economic development / Os fatores determinantes na geração de retornos de capital investido frente aos riscos assumidos nas instituições financeiras têm sido tema amplamente discutido nas finanças corporativas. O objetivo desta pesquisa é compreender a contribuição dos fatores econômico-financeiros na explicação do desempenho do retorno ajustado ao risco do capital: RAROC (Risk-Adjusted Return On Capital). Neste contexto, a utilização desta métrica teve, como ponto de partida, o fundamento da gestão do capital em instituições financeiras sob os enfoques da alocação em riscos versus a maximização retorno. Para tanto, a pesquisa considera a amostra de onze bancos com ações negociadas na BM&FBOVESPA e distribuídos em três grupos: (i) grande, (ii) médio e (iii) pequeno porte, tendo o porte definido conforme critério do BACEN descrito na Relatório de Estabilidade Financeira. A análise dos fatores econômico-financeiros apoia-se nos fundamentos do modelo DuPont, partindo da decomposição do ROE (Return On Equity) para a calcular o RAROC em instituições financeiras, onde se consideram três fatores: i) alavancagem financeira do capital, sendo a razão entre os ativos alocados em riscos e o capital disponível para riscos; ii) rentabilidade dos ativos, apurada pela razão entre as receitas líquidas e os ativos ponderados pelos riscos, e iii) taxa de lucratividade, medindo a eficiência operacional e tributária a partir da razão entre o lucro econômico e as receitas líquidas. O período selecionado foi de 2010 a 2015, com dados semestrais obtidos nas Demonstrações Financeiras e nos Documentos de Gerenciamento de Riscos e Capital divulgados pelas instituições financeiras, sendo considerado como o período posterior à crise bancária de 2008 e 2009. A metodologia adotada é de natureza empírico-analítica e o tipo de pesquisa caracteriza-se como quantitativa, descritiva e documental. Os resultados obtidos com a utilização de técnicas estatísticas de correlação de Pearson (r) e regressão linear múltipla no método stepwise (r2 ajustado), bem como os testes de hipóteses, onde indicaram a existência de características próprias para os grupos estudados. O grupo de bancos de grande porte apresentou o fator de lucratividade como o de maior capacidade de explicação do RAROC com correlação de 0,982 e r2 de 96,3%, demonstrando assim que a gestão eficiente dos custos da estrutura se apresentou como um fator diferenciador na geração do retorno ajustado ao risco do capital. No que diz respeito ao grupo de bancos de médio porte, os fatores lucratividade e rentabilidade apresentaram moderada capacidade de explicação e bastante similares com r2 de 48,4% e 43,1%, respectivamente. No grupo de bancos de pequeno porte, o fator lucratividade apresentou alta capacidade de explicação com r2 de 76,1%. Deve-se considerar que o mercado de bancos de médio e pequeno porte é mais vulnerável às crises econômicas e com maior custo de captação, exigindo assim a busca contínua da alta especialização, diferenciação e flexibilidade nos seus negócios. A justificativa deste trabalho baseia-se na relevância e atualidade do tema para a comunidade acadêmica e pela representatividade da atividade bancária no desenvolvimento econômico do país

隨著金融市場的整合、金融控股公司的成立，保險公司、銀行與證券機構等的經營不再只是各自為政，其經營變化皆會影響到整體的經營成敗。子公司的經營應不再只是注重經營績效，還應納入各項經營風險的考量，在報酬與風險之間取得一個平衡點。 本研究主要是透過風險調整資本報酬(RAROC)，來測量在金控旗下產物保險公司經營績效之優劣。本文利用民國73年至93年的產物保險年鑑的財報資料，以RAROC及傳統財務比率，比較富邦公司與本國老公司經營績效之差異。 本文之實證研究結果發現如下： 1. 在傳統財務比率之下，富邦產物保險公司的經營能力與本國老公司大致相同，但獲利能力明顯優於本國老公司。 2. 在風險調整資本報酬比率下，營運部分之績效比較結果為： (1) 在全部業務之下，富邦產物保險公司與本國老公司大致相同。 (2) 在扣除分保業務之後，富邦產物明顯優於本國老公司 3. 在風險調整資本報酬比率下，富邦產物之投資方面的經營績效明顯優於本國老公司。 / After the renovation of financial market and the establishment of financial holding company in Taiwan, insurance companies, banks and security institutes will not operate independently, and their efficiency on operation will affect themselves. Subsidiary companies not only focus on efficiency on operation, but also measure variation of risk on operation to achieve a balance between risk and return. This study applies the concept of Risk-Adjusted Return on Capital (RAROC) to measure efficiency on operation of non-life insurance company in financial holding company. The empirical analysis is conducted based on the financial data of non-life insurance companies in Taiwan during the period of 1984-2003. The empirical results are summarized as follow. 1. Base on traditional financial ratios, the underwriting efficiency of Fubon is the same as the other companies, but in the part of investment, Fubon is more efficient than other companies. 2. Based on Risk-Adjusted Return on Capital for measuring underwriting efficiency: (1) Fubon and old local companies are the same efficient for total business. (2) Fubon is significantly more efficient than other companies for the retained business. 3. Based on Risk-Adjusted Return on Capital for measuring investment efficiency, Fubon is better than other companies.

This chapter contains the capital theory controversy that took place among the most importanteconomists from the universities of Cambridge (UK) and Cambridge (Mass.). Firstly, we presentthe neoclassical propositions which are summarized in the neoclassical parables. The second section contains Robinson’s criticism of the neoclassical capital theory and Garegnani’s criticismof the decreasing marginal productivity theory. Thirdly, we summarize Samuelson’s attempt to validate the neoclassical production function and his main mistakes. The fourth section presents Solow’s response and Nell’s criticism. Finally, in the fifth section, we present the main contributions to the capital theory controversy. / Este capítulo presenta el contenido de la controversia en torno a la teoría del capital que se llevó a cabo entre los economistas más importantes de las universidades de Cambridge (Inglaterra) yCambridge (Estados Unidos). Primero se presenta las proposiciones fundamentales de la teoría neoclásica, es decir, las parábolas neoclásicas. La segunda sección aborda las críticas de Joan Robinson a la teoría neoclásica del capital y las críticas de Garegnani a la teoría de la productividad marginal decreciente. En la tercera parte, se expone el intento de Samuelson de validar la funciónde producción neoclásica y los principales errores que él comete. La cuarta sección presenta la respuesta de Solow y la crítica de Nell. Finalmente, en la quinta sección, se señalan los principales aportes de esta controversia sobre la teoría del capital.

This thesis deals with company capital structure, that is characterized according to methods of horizontal and vertical analysis. Then it deals with prices of particular capital items, costs for capital and influeces on business performance, it means with the calculation of economic value added. Theoretical part describes capital structure items in general, prices of particular items of capital, costs for capital and particular methods for EVA calculation, it means both EVA entity and EVA equity. Practical part characterizes individual items of capital structure and application of chosen model, that is the second model for EVA calculation {--} EVA equity {--} on a concrete company. This calculation was processed through benchmarking on websides of Departement of industry and Trade. The model was applicated on a company, that deals with production of motor and joining vehicles, machines production, machineries production and means of transport repairs {--} ČZ, a.s.

The purpose of the study is to examine if the gender composition of a board has an effect on a company’s financial performance by analyzing their operating margin and return on capital employed (ROCE). The study is based on a quantitative method, studying companies listed on the Stockholm Stock Exchange. Previous research has not been studying the gender composition of boards of Swedish companies and its effect on the company's financial performance in regard to their operating margin and return on capital employed. Therefore, this study has examined that in order to draw a conclusion regarding its possible effects. The data that is collected will be used as support in the analysis in order to understand how the current composition and effects are connected. This study will contribute with knowledge for companies in Sweden regarding gender composition of boards and the possible effects on their financial performance. But also, as support for the ongoing discussion regarding board composition and the current inequality in gender representation. In conclusion the study shows that return on capital employed and the proportion of women in the board has a positive relationship. Meaning that the bigger proportion of women in a board, the better return on capital employed the company has. However, for operating margin there was not a significant relationship and therefore a conclusion regarding that cannot be made.

Diploma thesis deals with analysis of investment opportunities in the capital markets. The aim of this thesis is to devise an appropriate investment strategy and financial investment of the company in the capital markets given to the current economic situation. This thesis takes into account the concrete requirements defined by investor.

The growing lack of confidence in public companies arises from the recent accounting scandals and corporate collapses, which have been attributed to the consequences of separation of ownership and control in modern firms. Agency theory predicts a conflict of interest between managers and shareholders that leads to agency costs and weak performance. This study used agency, stakeholders', and stewardship theories as the theoretical framework and multiple regression analysis to examine the relationship between corporate governance mechanisms and organizational performance in nonfinancial firms listed on the Nigerian Stock Exchange. The results of the study could help clarify understanding of corporate governance to managers, investors, and regulators who seek to understand how corporate governance impact firms' performance. In this study, corporate governance mechanisms included board independence, audit committee independence, board size, number of board meetings, and executive compensation. The data were collected from the firms' published accounts on their websites and on the archives of the Nigerian Stock Exchange for a period starting from January 1, 2011 to December 31, 2015. The measures of financial performance in the study were return on assets, return on capital employed, and Tobin's Q. The study found a positive but not statistically significant relationship between corporate governance mechanisms and financial performance. This study has implications for positive social change by showing managers and other stakeholders of firms how a good corporate governance system assures investor confidence, employee loyalty and commitment, the reduction in conflict of interest and agency costs, and a strong financial performance.

Return on Capital Employed (ROCE) is a popular financial instrument and communication tool for the appraisal of companies. Often, companies management and other practitioners use untested rules and behavioural approach when investigating the key determinants of ROCE, instead of the scientific statistical paradigm. The aim of this dissertation was to identify and quantify key determinants of ROCE of individual companies listed on the Johannesburg Stock Exchange (JSE), by comparing classical multiple linear regression, principal components regression, generalized least squares regression, and robust maximum likelihood regression approaches in order to improve companies decision making. Performance indicators used to arrive at the best approach were coefficient of determination ( ), adjusted ( , and Mean Square Residual (MSE). Since the ROCE variable had positive and negative values two separate analyses were done. The classical multiple linear regression models were constructed using stepwise directed search for dependent variable log ROCE for the two data sets. Assumptions were satisfied and problem of multicollinearity was addressed. For the positive ROCE data set, the classical multiple linear regression model had a of 0.928, an of 0.927, a MSE of 0.013, and the lead key determinant was Return on Equity (ROE),with positive elasticity, followed by Debt to Equity (D/E) and Capital Employed (CE), both with negative elasticities. The model showed good validation performance. For the negative ROCE data set, the classical multiple linear regression model had a of 0.666, an of 0.652, a MSE of 0.149, and the lead key determinant was Assets per Capital Employed (APCE) with positive effect, followed by Return on Assets (ROA) and Market Capitalization (MC), both with negative effects. The model showed poor validation performance. The results indicated more and less precision than those found by previous studies. This suggested that the key determinants are also important sources of variability in ROCE of individual companies that management need to work with. To handle the problem of multicollinearity in the data, principal components were selected using Kaiser-Guttman criterion. The principal components regression model was constructed using dependent variable log ROCE for the two data sets. Assumptions were satisfied. For the positive ROCE data set, the principal components regression model had a of 0.929, an of 0.929, a MSE of 0.069, and the lead key determinant was PC4 (log ROA, log ROE, log Operating Profit Margin (OPM)) and followed by PC2 (log Earnings Yield (EY), log Price to Earnings (P/E)), both with positive effects. The model resulted in a satisfactory validation performance. For the negative ROCE data set, the principal components regression model had a of 0.544, an of 0.532, a MSE of 0.167, and the lead key determinant was PC3 (ROA, EY, APCE) and followed by PC1 (MC, CE), both with negative effects. The model indicated an accurate validation performance. The results showed that the use of principal components as independent variables did not improve classical multiple linear regression model prediction in our data. This implied that the key determinants are less important sources of variability in ROCE of individual companies that management need to work with. Generalized least square regression was used to assess heteroscedasticity and dependences in the data. It was constructed using stepwise directed search for dependent variable ROCE for the two data sets. For the positive ROCE data set, the weighted generalized least squares regression model had a of 0.920, an of 0.919, a MSE of 0.044, and the lead key determinant was ROE with positive effect, followed by D/E with negative effect, Dividend Yield (DY) with positive effect and lastly CE with negative effect. The model indicated an accurate validation performance. For the negative ROCE data set, the weighted generalized least squares regression model had a of 0.559, an of 0.548, a MSE of 57.125, and the lead key determinant was APCE and followed by ROA, both with positive effects.The model showed a weak validation performance. The results suggested that the key determinants are less important sources of variability in ROCE of individual companies that management need to work with. Robust maximum likelihood regression was employed to handle the problem of contamination in the data. It was constructed using stepwise directed search for dependent variable ROCE for the two data sets. For the positive ROCE data set, the robust maximum likelihood regression model had a of 0.998, an of 0.997, a MSE of 6.739, and the lead key determinant was ROE with positive effect, followed by DY and lastly D/E, both with negative effects. The model showed a strong validation performance. For the negative ROCE data set, the robust maximum likelihood regression model had a of 0.990, an of 0.984, a MSE of 98.883, and the lead key determinant was APCE with positive effect and followed by ROA with negative effect. The model also showed a strong validation performance. The results reflected that the key determinants are major sources of variability in ROCE of individual companies that management need to work with. Overall, the findings showed that the use of robust maximum likelihood regression provided more precise results compared to those obtained using the three competing approaches, because it is more consistent, sufficient and efficient; has a higher breakdown point and no conditions. Companies management can establish and control proper marketing strategies using the key determinants, and results of these strategies can see an improvement in ROCE. / Mathematical Sciences / M. Sc. (Statistics)

Return on Capital Employed (ROCE) is a popular financial instrument and communication tool for the appraisal of companies. Often, companies management and other practitioners use untested rules and behavioural approach when investigating the key determinants of ROCE, instead of the scientific statistical paradigm. The aim of this dissertation was to identify and quantify key determinants of ROCE of individual companies listed on the Johannesburg Stock Exchange (JSE), by comparing classical multiple linear regression, principal components regression, generalized least squares regression, and robust maximum likelihood regression approaches in order to improve companies decision making. Performance indicators used to arrive at the best approach were coefficient of determination ( ), adjusted ( , and Mean Square Residual (MSE). Since the ROCE variable had positive and negative values two separate analyses were done. The classical multiple linear regression models were constructed using stepwise directed search for dependent variable log ROCE for the two data sets. Assumptions were satisfied and problem of multicollinearity was addressed. For the positive ROCE data set, the classical multiple linear regression model had a of 0.928, an of 0.927, a MSE of 0.013, and the lead key determinant was Return on Equity (ROE),with positive elasticity, followed by Debt to Equity (D/E) and Capital Employed (CE), both with negative elasticities. The model showed good validation performance. For the negative ROCE data set, the classical multiple linear regression model had a of 0.666, an of 0.652, a MSE of 0.149, and the lead key determinant was Assets per Capital Employed (APCE) with positive effect, followed by Return on Assets (ROA) and Market Capitalization (MC), both with negative effects. The model showed poor validation performance. The results indicated more and less precision than those found by previous studies. This suggested that the key determinants are also important sources of variability in ROCE of individual companies that management need to work with. To handle the problem of multicollinearity in the data, principal components were selected using Kaiser-Guttman criterion. The principal components regression model was constructed using dependent variable log ROCE for the two data sets. Assumptions were satisfied. For the positive ROCE data set, the principal components regression model had a of 0.929, an of 0.929, a MSE of 0.069, and the lead key determinant was PC4 (log ROA, log ROE, log Operating Profit Margin (OPM)) and followed by PC2 (log Earnings Yield (EY), log Price to Earnings (P/E)), both with positive effects. The model resulted in a satisfactory validation performance. For the negative ROCE data set, the principal components regression model had a of 0.544, an of 0.532, a MSE of 0.167, and the lead key determinant was PC3 (ROA, EY, APCE) and followed by PC1 (MC, CE), both with negative effects. The model indicated an accurate validation performance. The results showed that the use of principal components as independent variables did not improve classical multiple linear regression model prediction in our data. This implied that the key determinants are less important sources of variability in ROCE of individual companies that management need to work with. Generalized least square regression was used to assess heteroscedasticity and dependences in the data. It was constructed using stepwise directed search for dependent variable ROCE for the two data sets. For the positive ROCE data set, the weighted generalized least squares regression model had a of 0.920, an of 0.919, a MSE of 0.044, and the lead key determinant was ROE with positive effect, followed by D/E with negative effect, Dividend Yield (DY) with positive effect and lastly CE with negative effect. The model indicated an accurate validation performance. For the negative ROCE data set, the weighted generalized least squares regression model had a of 0.559, an of 0.548, a MSE of 57.125, and the lead key determinant was APCE and followed by ROA, both with positive effects.The model showed a weak validation performance. The results suggested that the key determinants are less important sources of variability in ROCE of individual companies that management need to work with. Robust maximum likelihood regression was employed to handle the problem of contamination in the data. It was constructed using stepwise directed search for dependent variable ROCE for the two data sets. For the positive ROCE data set, the robust maximum likelihood regression model had a of 0.998, an of 0.997, a MSE of 6.739, and the lead key determinant was ROE with positive effect, followed by DY and lastly D/E, both with negative effects. The model showed a strong validation performance. For the negative ROCE data set, the robust maximum likelihood regression model had a of 0.990, an of 0.984, a MSE of 98.883, and the lead key determinant was APCE with positive effect and followed by ROA with negative effect. The model also showed a strong validation performance. The results reflected that the key determinants are major sources of variability in ROCE of individual companies that management need to work with. Overall, the findings showed that the use of robust maximum likelihood regression provided more precise results compared to those obtained using the three competing approaches, because it is more consistent, sufficient and efficient; has a higher breakdown point and no conditions. Companies management can establish and control proper marketing strategies using the key determinants, and results of these strategies can see an improvement in ROCE. / Mathematical Sciences / M. Sc. (Statistics)

Submitted by Minoru Ito (minoruito@gmail.com) on 2015-02-26T16:18:44Z No. of bitstreams: 1 Minoru Ito - Dissertação.pdf: 3146333 bytes, checksum: 2be44b6347010be421091aa520f3aef9 (MD5) / Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2015-03-02T19:32:52Z (GMT) No. of bitstreams: 1 Minoru Ito - Dissertação.pdf: 3146333 bytes, checksum: 2be44b6347010be421091aa520f3aef9 (MD5) / Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2015-03-02T19:33:16Z (GMT) No. of bitstreams: 1 Minoru Ito - Dissertação.pdf: 3146333 bytes, checksum: 2be44b6347010be421091aa520f3aef9 (MD5) / Made available in DSpace on 2015-03-02T19:33:33Z (GMT). No. of bitstreams: 1 Minoru Ito - Dissertação.pdf: 3146333 bytes, checksum: 2be44b6347010be421091aa520f3aef9 (MD5) Previous issue date: 2015-02-26 / As concessões e as Parcerias Público-Privadas (PPP) são mecanismos cada vez mais utilizados pelo setor público para alavancar os investimentos em infraestrutura no país. Para que haja viabilidade econômica das mesmas, as suas taxas internas de retorno (TIR) apresentam-se como variáveis que precisam refletir os riscos e a realidade do negócio. O presente estudo busca analisar as taxas de retorno utilizadas para a modelagem das tarifas-teto do setor de rodovias federais frente às especificidades do seu mercado. Para tal, são seguidas três frentes: a primeira é analisar a metodologia da taxa de retorno utilizada para a modelagem das concessões mais recentes de rodovias; a segunda é estimar uma taxa de retorno a partir de pesquisa bibliográfica; e a terceira é, por meio de dados de rentabilidade de balanços de concessionárias do setor, observar se as taxas de retorno das primeiras concessões foram devidamente calculadas na época. Na dissertação, concluímos que a atual metodologia da taxa de retorno do Tesouro Nacional pode ser aprimorada, principalmente em relação aos parâmetros de grau de alavancagem e capital de terceiros, e observamos que a taxa de retorno tem se aproximado do custo de oportunidade do setor ao longo das últimas etapas de concessão. O estudo visa contribuir para o debate sobre a rentabilidade dos projetos de infraestrutura rodoviária, em meio a um período de intensos investimentos no setor. / Concessions and Public-Private Partnerships (PPP) are mechanisms increasingly used by the public sector to enhance the investments in infrastructure in Brazil. To achieve economic viability in these projects, their internal rates of return (IRR) are variables which must reflect the risks and reality of the business. The present study seeks to analyse the IRRs used for modeling the price-caps of the federal highways’ sector, under the specificities of such market. For this purpose, three approaches are pursued: the first one analyses the methodology of IRR calculation applied for modelling the most recent highway concessions; the second estimates an IRR based on bibliographic research; and the third makes use of data acquired from the balance sheets from the sector`s concessionaries, to observe if the IRR for the f irst concessions of federal highways were properly calculated at the time. In this dissertation, we concluded that the current National T reasury´s methodology of the rate of return can be improved, especially in relation to parameters like leverage and debt, and we observed that the rate of return has come closer to the opportunity cost for the sector throughout the last concession rounds. This study aims to contribute to the debate on the profitability of road infrastructure projects, a midst a period of intense investments in the sector.