The purpose of this paper is to examine the interest rate transmission mechanism for South Africa as an emerging economy in a pre-repo and repo system. It explains how the money market rate is transmitted to the retail interest rates both in the long-run and short-run and tests the symmetric and asymmetric interest rate pass-through using the Scholnick (1996) ECM and the Wang and Lee (2009) ECM-EGARCH (1, 1)-M methodology. This permitted the examination of the impact of interest rate volatility, along with the leverage effect. An incomplete pass-through is found in the short-run. From the entire sample period, a symmetric adjustment is found in the deposit rate, which had upward rigidity adjustment, while an asymmetric adjustment is found in the lending rate, with a downward rigidity adjustment. All the adjustments supported the collusive pricing arrangements. According to the conditional variance estimation of the ECM-EGARCH (1, 1), negative volatility impact and leverage effect are present and influential only in the deposit interest rate adjustment process in South Africa.

This study examines the American Dollar (USD) denominated currency returns of five developing market currencies for the presence of the day-of-the-week effect. Daily data from January 1995 to February 2008 is examined, and is split into two subperiods, SP1 (1995 - 2002) and SP2 (2003 - February 2008). Currency returns are non-normally distributed across the full data set and SP1 , but tend towards normality in SP2. As such non-parametric tests are used to test the equality of the first four moments across days of the week. Tests on the first moment show that two of the currencies do not show any evidence of the day-of-the-week effect. However, evidence of the day-of-the-week effect is found in the other three currencies in SP1, although the effect disappears or weakens significantly in SP2. Little evidence of the day-of-the-week effect is found in tests on the second moment. The hypothesis of equal higher moments across currency returns is rejected for almost all of the weekday pairs for all five currencies in SP1 , but in SP2 the hypothesis of equal higher moments can only be rejected for a single pair of weekdays for one currency. This indicates the disappearance of the day-of-the-week effect across higher moments in SP2. Thus, the study finds that the day-of-the-week effect is present across the first moment and higher moments in the returns to most currencies in SP1 , but has disappeared for all five currencies in SP2. / KMBT_363 / Adobe Acrobat 9.54 Paper Capture Plug-in

The aim of this thesis is to evaluate the possibility of household investment in the money market in the Czech Republic. In the theoretical section we can find details of the cash market and its segments. Followed by financial institutions and relevant indicators influencing investor decisions. The practical part is focused on specific financial products. They are mutually compared and evaluated in terms of availability and suitability for the small investor. Return, risk and liquidity are also taken into account.

published_or_final_version / Business Administration / Master / Master of Business Administration

i Abstract Recent financial crisis resulting in global financial instability pointed at the importance of growing shadow banking. Shadow banking activities are gen- erally defined as banking-like activities outside of regulated banking. In this thesis, we study theoretical background of shadow banking, its regulation and supervision. Despite the data availability problem, a qualitative analysis is performed to estimate the volume of the European and the U.S. shadow bank- ing sectors from 2006 until 2013 Q2. European shadow banking system hit its bottom of EUR 8.3 trillion (19% of total European bank assets) in 2008 Q4. Nowadays, it equals to EUR 9.3 trillion (21% of total European bank assets). U.S. shadow banking sector attained its maximum of USD 20.7 trillion (163% of total U.S. bank assets) in 2008 Q1. Nowadays, it equals to USD 15.6 tril- lion which also equals to total U.S. bank assets. Moreover, we concentrate on Chinese money market funds and French and UK repo markets, since these represent an important part of shadow banking. Quantitative analysis studies relationships among traditional banking, shadow banking and economy itself in France and UK. Results show that if repo transactions, GDP and government debt increase, total bank assets increase. Furthermore, if money market fund assets decrease and...

Made available in DSpace on 2015-12-03T18:35:29Z (GMT). No. of bitstreams: 1 Marcos_de_Mello_Liberato.pdf: 734486 bytes, checksum: cf5e35324052e71d3641a4810970e357 (MD5) Previous issue date: 2013-10-15 / Pension Funds in Brazil are presented as large institutional investors, moving a significant sum of money in the financial market. Investment decisions made by its managers should generate positive returns in order to ensure a dignified retirement to its participants and beneficiaries. The corporate governance structure of pension funds and their mechanisms are essential elements in the management of these entities, and the consequent impact exerted on their performance. The objective of this research is to study the relationship between structure and corporate governance mechanisms and performance of pension funds in Brazil. This is an empirical study, with quantitative treatment of the data by use of linear regression with panel data. The period of analysis included the years 2008 to 2012. The results were favorable to the affirmative conclusion regarding the existence of an associative relationship between corporate governance mechanisms and their performance / As Entidades Fechadas de Previd??ncia Complementar no Brasil, conhecidas como fundos de pens??o, apresentam-se como grandes investidores institucionais, movimentando uma significativa soma de dinheiro no mercado financeiro. As decis??es de investimento tomadas por seus gestores devem gerar retornos positivos, de forma a garantir uma aposentadoria digna a seus participantes e benefici??rios. A estrutura de governan??a corporativa dos fundos de pens??o, e seus mecanismos, constituem elementos fundamentais na gest??o dessas institui????es, e no consequente impacto exercido sobre seu desempenho. O objetivo desta pesquisa ?? analisar a rela????o entre a estrutura e os mecanismos de governan??a corporativa e o desempenho dos fundos de pens??o no Brasil. Este ?? um estudo emp??rico anal??tico, com tratamento quantitativo dos dados, pelo uso da t??cnica de regress??o linear com dados em painel, cujo per??odo de an??lise compreendeu os anos de 2008 a 2012. Os resultados obtidos foram favor??veis ?? conclus??o afirmativa a respeito da exist??ncia de uma rela????o associativa entre os mecanismos de governan??a corporativa e o desempenho dessas entidades

Submitted by Elba Lopes (elba.lopes@fecap.br) on 2016-06-20T15:25:30Z No. of bitstreams: 2 Michele_Svaiger_Teixeira.pdf: 1276451 bytes, checksum: 33e80e789182b470b1b290f8dfa5e294 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2016-06-20T15:25:30Z (GMT). No. of bitstreams: 2 Michele_Svaiger_Teixeira.pdf: 1276451 bytes, checksum: 33e80e789182b470b1b290f8dfa5e294 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2015-08-27 / This dissertation analyzes the equity issuance activity (IPOs and follow-ons) relation with economics fundamentals and investor sentiment between 2004 and 2013 in the Brazilian market. Measures of the economy such as GDP (Gross Domestic Product), Selic rate, Gross Fixed Capital Formation (FBCF), exchange rate variance and Bovespa Index were associated to IPOs and follow-ons that occurred in the analyzed period summarized quarterly in monetary and quantitative terms. A modest relation between measures of the economy and equity issuance activity was observed, roughly 30%. The Optimism Index (IO) developed by NEFIN and the Consumer Sentiment Index (ICC) calculated by Fecomercio was defined as sentiment measures on the model and they were not statistically significant in the empirical analysis, contradicting studies about investor sentiment relation with the financial market. / Esta disserta????o analisa a rela????o da atividade de emiss??o de a????es (IPOs e follow-ons) com as vari??veis macroecon??micas e com o sentimento do mercado entre os anos de 2004 e 2013 no Brasil. Fatores macroecon??micos como PIB (Produto Interno Bruto), Taxa Selic, Forma????o Bruta de Capital Fixo (FBCF), varia????o cambial e o ??ndice Bovespa foram relacionados aos IPOs e follow-ons ocorridos no per??odo e sumarizados trimestralmente em termos monet??rios e quantitativos. Identificou-se uma modesta rela????o dessas vari??veis com a atividade de emiss??o de a????es em torno de 30%. O ??ndice de Otimismo (IO) desenvolvido pelo NEFIN e o ??ndice de Confian??a do Consumidor (ICC) apurado pela Fecomercio representaram o sentimento de mercado e n??o possu??ram signific??ncia estat??stica na an??lise emp??rica, contrariando estudos acerca da representatividade do sentimento do investidor no mercado financeiro.

Submitted by Filipe dos Santos (fsantos@pucsp.br) on 2018-05-07T12:56:34Z No. of bitstreams: 1 Rosana Passos de Pádua.pdf: 2042065 bytes, checksum: 9d29868f47767b9c0fc87f79b6b1a55c (MD5) / Made available in DSpace on 2018-05-07T12:56:34Z (GMT). No. of bitstreams: 1 Rosana Passos de Pádua.pdf: 2042065 bytes, checksum: 9d29868f47767b9c0fc87f79b6b1a55c (MD5) Previous issue date: 2018-03-14 / Brazil is facing many discussions about the future of social security, and in this context, complementary social security becomes even more relevant; due to this, a great interest arose in studying the accounting of pension funds in the light of Brazilian and international rules, IAS 19 and IAS 26. The research problem consisted in understanding and seeking alternatives to the difficulty of pension fund managers to comply with the rules of the financial market and to mark-to-market for long-term investments with the current conditions of interest rate volatility, in the same time there is no mark-to-market of actuarial liabilities, causing an actuarial mismatching. The research was conducted through a case study based on a six-year pension fund financial statement and the outcome of the case study demonstrated that a possibility to minimize this effect and reduce the risk of sponsors and participants being called to cover the deficits, would be the accounting of the counterpart of the mark-to-market of the asset in a transitional liability account as a provision, without impacting the results of the pension funds / O Brasil está passando por um momento de muitas discussões sobre o futuro da previdência social e nesse contexto, a previdência complementar torna-se ainda mais relevante; em virtude disso, surgiu o grande interesse em estudar a contabilidade dos fundos de pensão à luz das regras brasileiras e das internacionais, IAS 19 e IAS 26. O problema de pesquisa consistiu em compreender e buscar alternativa para a dificuldade dos gestores dos fundos de pensão em obedecer às regras do mercado financeiro e marcar a mercado os investimentos de longo prazo com as condições de volatilidade de taxas de juros, sem que haja a marcação a mercado dos passivos atuariais, causando desequilíbrio atuarial. A pesquisa foi realizada através de estudo de caso, com base em demonstrações financeiras de seis anos de uma entidade privada e o resultado do estudo de caso demonstrou que uma possibilidade para minimizar esse efeito e reduzir o risco de patrocinadores e participantes serem chamados a cobrir os déficits, seria a contabilização da contrapartida da marcação a mercado do ativo em conta transitória de passivo a título de provisão, sem impactar o patrimônio dos fundos de pensão

Made available in DSpace on 2014-06-11T19:26:16Z (GMT). No. of bitstreams: 0 Previous issue date: 2012-12-21Bitstream added on 2014-06-13T19:13:20Z : No. of bitstreams: 1 costa_af_me_bauru.pdf: 1184483 bytes, checksum: 1783e7ab1d2b2b0b7dab05babd2093e8 (MD5) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / A previsão de séries temporais financeiras é uma das questões mais pesquisadas no campo das finanças, sobretudo, no que diz respeito ao mercado acionário e à análise de riscos. Para tanto, essas pesquisas envolvem desde modelos estatísticos e econométricos até modelos de inteligência artificial, como as redes neurais dinâmicas. Nesse sentido este estudo tem o propósito de desenvolver e aplicar dois modelos de redes neurais artificiais dinâmicas, a rede neural focada atrasada no tempo - FTDNN (focused time delay neural network) e a rede neural auto regressiva com entradas exógenas - NARX (nonlinear autoregressive network with exogenous inputs) para previsão de séries temporais financeiras, tendo como padrão de referência de desempenho mínimo um modelo estatístico tradicional do tipo ARMA-GARCH. Essa abordagem camparativa também considera três modalidades diferentes de transformação de dados na fase pré-processamento das redes: as diferenças de primeira ordem, os retornos logarítmicos e a transformação Box-Cox, buscando analisar o impacto de cada uma delas no desempenho preditivo das redes neurais. Também propõe uma abordagem neural para o processo de reversão dos dados previstos e uma métrica de erro capaz de verificar o desempenho preditivo das redes neurais e sua capacidade de captar tendências de curto prazo e eficiência negocial. Em sentido amplo, os resultados obtidos indicam que a rede NARX apresenta melhor desempenho preditivo que a rede FTDNN, sobretudo, no que diz respeito à captura de tendências; que a transformações de dados podem melhorar o nível de acurácia das previsões em ambas as redes e que a transformação por retornos logarítimos gera os melhores desempenhos. Quanto ao processo de reversão dos dados previstos para a escala da série original, o método neural proposto foi bem sucedido apenas para a transformação Box-cox / Financial time-series forescasting is one of the most researched issues in finances, mainly with regard to the stock market and risk analysis. Therefore, these studies involve from statistical and econometric models up to artificial intelligence models, such as dynamic neural networks. In this sense, this study aims to develop and apply two models of dynamic artificial neural networks, FTDNN (focused time delay neural network) and NARX (nonlinear autoregressive network with exagenous inputs) for financial time series forescasting, with a traditional statistical model such as ARMAGARCH as the benchmark for minimum performance. The comparative approach also considers three diferent types of data transformation in the pre-processing phase of the networks: first order differences, logarithmics returns and Box-Cox transformation, and tries to analyze the impact of each on the predictive performance of the neural networks. It also proposes a neural approach to the process of reversing the predicted data set, and an error metric that could be able to verify the predictive performance of neural networks and its ability to capture short-term trends and negotiation efficiency. In a bropad sense, the reults indicate that the NARX network network performs beter than the FTDNN, especially with regard to capturing trends; that data transformations may improve the forescasting accuracy in both networks, and that the logarithmics returns transformation generates the best prediction performance. Regarding the process of reversing the predicted data for the scale of the original series, the neural method proposed succeeded only for Box-Cox transformation

Orientador: Antonio Fernando Crepaldi / Banca: Rogério Andrade Flauzino / Banca: José Alfredo Colovan Ulson / Resumo: A previsão de séries temporais financeiras é uma das questões mais pesquisadas no campo das finanças, sobretudo, no que diz respeito ao mercado acionário e à análise de riscos. Para tanto, essas pesquisas envolvem desde modelos estatísticos e econométricos até modelos de inteligência artificial, como as redes neurais dinâmicas. Nesse sentido este estudo tem o propósito de desenvolver e aplicar dois modelos de redes neurais artificiais dinâmicas, a rede neural focada atrasada no tempo - FTDNN (focused time delay neural network) e a rede neural auto regressiva com entradas exógenas - NARX (nonlinear autoregressive network with exogenous inputs) para previsão de séries temporais financeiras, tendo como padrão de referência de desempenho mínimo um modelo estatístico tradicional do tipo ARMA-GARCH. Essa abordagem camparativa também considera três modalidades diferentes de transformação de dados na fase pré-processamento das redes: as diferenças de primeira ordem, os retornos logarítmicos e a transformação Box-Cox, buscando analisar o impacto de cada uma delas no desempenho preditivo das redes neurais. Também propõe uma abordagem neural para o processo de reversão dos dados previstos e uma métrica de erro capaz de verificar o desempenho preditivo das redes neurais e sua capacidade de captar tendências de curto prazo e eficiência negocial. Em sentido amplo, os resultados obtidos indicam que a rede NARX apresenta melhor desempenho preditivo que a rede FTDNN, sobretudo, no que diz respeito à captura de tendências; que a transformações de dados podem melhorar o nível de acurácia das previsões em ambas as redes e que a transformação por retornos logarítimos gera os melhores desempenhos. Quanto ao processo de reversão dos dados previstos para a escala da série original, o método neural proposto foi bem sucedido apenas para a transformação Box-cox / Abstract: Financial time-series forescasting is one of the most researched issues in finances, mainly with regard to the stock market and risk analysis. Therefore, these studies involve from statistical and econometric models up to artificial intelligence models, such as dynamic neural networks. In this sense, this study aims to develop and apply two models of dynamic artificial neural networks, FTDNN (focused time delay neural network) and NARX (nonlinear autoregressive network with exagenous inputs) for financial time series forescasting, with a traditional statistical model such as ARMAGARCH as the benchmark for minimum performance. The comparative approach also considers three diferent types of data transformation in the pre-processing phase of the networks: first order differences, logarithmics returns and Box-Cox transformation, and tries to analyze the impact of each on the predictive performance of the neural networks. It also proposes a neural approach to the process of reversing the predicted data set, and an error metric that could be able to verify the predictive performance of neural networks and its ability to capture short-term trends and negotiation efficiency. In a bropad sense, the reults indicate that the NARX network network performs beter than the FTDNN, especially with regard to capturing trends; that data transformations may improve the forescasting accuracy in both networks, and that the logarithmics returns transformation generates the best prediction performance. Regarding the process of reversing the predicted data for the scale of the original series, the neural method proposed succeeded only for Box-Cox transformation / Mestre