The aim of this master paper is to reveal the role of a judge. In the first part of the paper the ideas of social civil procedure school (that is essential in the Lithuanian Republic Civil procedure code) defining an active role in civil procedure and the model of civil procedure of Lithuanian Republic are discussed. The second part of the paper deals with analysis of stages of the civil procedure. By analyzing these stages the author of the paper tries to disclose by which means provided in law the judge realizes his (hers) performing role in the procedure. Also the intensity of the judge role depending on the stage of the civil procedure is shown. Attention is paid to certain categories of cases that influence the extension of the judge’s activity and the difference of performing intensity depending on contentious proceedings as well. In the third part of the paper the possibilities of making default judgment and judicial penalties assigning as means helping to control parties that overindulge processing right or do not care about the progress of proceedings are discussed.

We consider a model of active asset management in which mutual fund managers exert unobservable effort to earn excess returns. Investors allocate capital to actively managed funds and passively managed products. In equilibrium, investors are indifferent between investing an additional dollar with an active manager or with a passively managed product. As passively managed products become more attractive to investors, active managers’ revenues from portfolio-management services fall, reducing their effort incentives. More-severe decreasing-returns-to-scale are also associated with reduced incentives and increased moral hazard. Performance-based fees and holdings-based data are all unlikely to mitigate moral hazard.

Pension is a subject that soon or later affects all individuals in society. Within the premium pension system mutual fund fees are an important factor to consider since it can erode savings. This study investigates fees and performance of all mutual funds that existed in the premium pension system (PPS) between 2004 and 2016. Risk-adjusted performance and fees are adjusted to reflect the discount that is given for fees within the premium pension system to reflect actual investor experiences. The data needed to make these adjustments were obtained from the Swedish Pension Agency. The main purpose of this study is to investigate if there is a relationship between fee and risk-adjusted return within the Swedish premium pension system. Further on this study aims to explain what mutual fund characteristics can be used to predict performance and fees within the premium pension system.Theories used in this study are efficient market hypothesis, agency theory, behavioral finance, economies of scale and portfolio theory. The factors from the Carhart 4-factor model is used to construct the factor model utilized in this study to estimate risk-adjusted returns. This study adapts a quantitative research method and panel data regressions were conducted to determine how fee and risk-adjusted performance is related to various mutual fund characteristics. Hausman tests were conducted to evaluate if the fixed effects model or random effects model was the most appropriate to use. The result of the Hausman test proved that fixed effect model was the most appropriate model to use.This study will draw conclusions about whether the fee that the mutual fund companies charge can be justified given their risk-adjusted performance. The results for the sample of all mutual funds and the sample of equity funds imply that there exists a positive relationship between fee after discount and performance. Therefore, mutual funds in the premium pension system compensate for increasing fees with a higher risk-adjusted return. The sample of balanced funds differs since there is a negative relationship between risk-adjusted returns and fees. This study finds that size is a determinant of risk-adjusted performance, with larger mutual fund performing better than smaller funds. Because of this finding, it can be concluded that economies of scale do exist among the mutual funds in the premium pension system. Actively managed mutual funds charge higher mutual fund fees on average than passively managed funds. Further on, there is significant evidence that actively managed equity funds perform worse than passively managed equity funds. This suggests that investors are better off investing into cheaper equity index funds rather than expensive actively managed equity funds.

Against a backdrop of controversy surrounding market timing, this research assesses the merits of a tactical asset allocation strategy for the South African market. The purpose of this research is to assess whether a simple quantitative method - initially presented by Faber (2007) - can successfully reduce volatility and increase returns of selected indices within the Johannesburg Stock Exchange (JSE). The All Share (ALSI), Financial&Industrial (FINI), Resource (RESI), Africa Gold Mining (AGMI), Government Bond (GOVI) and Property Unit Trust (PUTI) indices were examined. A strategy based on a ten-month simple moving average was compared against a buy-and-hold strategy, with results presented for these strategies both excluding and including transaction costs. The strategies were tested over a 50-year period from 1961 to 2010. The results show that superior risk-adjusted returns are possible even in the presence of high transaction costs. Further insights suggest that tactical asset allocation strategies yield improved performances when used in specific sectors and/or asset classes, instead of in consolidated sectors represented by the market.Copyright / Dissertation (MBA)--University of Pretoria, 2012. / Gordon Institute of Business Science (GIBS) / unrestricted

In active portfolio management, fund managers seek to follow an investment strategy with the objective of outperforming an investment benchmark index. Opportunities to outperform a benchmark in active fund management is made possible through crosssectional dispersion of returns in the market. It is cross-sectional volatility of returns that allows fund managers to identify changing trends in market relationships and to take advantage of market opportunities.Quarterly active share and active return data of Domestic General Equity funds was used to determine whether the level of active share and active return has a correlation with volatility measures such as cross-sectional variance of returns or the South African Volatility Index (SAVI). The actively-managed funds’ outperformance of the benchmark index during periods of differing cross-sectional variance was also looked at. Lastly, the possibility of whether market volatility can be used to inform fund investment decisions was also examined.The findings in this study are that there is no significant relationship between the crosssectional variance of returns, active share and active returns. In measuring fund performance in times of differing cross-sectional dispersion and breaking the analysis period into such intervals rather than as a continuous time series, active funds outperform the benchmark index during periods of low and moderate cross-sectional variance. The SAVI can be used as a fairly accurate and readily available approximation of cross-sectional variance. / Dissertation (MBA)--University of Pretoria, 2012. / Gordon Institute of Business Science (GIBS) / unrestricted

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[pt] Esta dissertação apresenta um panorama geral sobre o processo de gerenciamento ativo de carteiras, focando exclusivamente nas duas primeiras fases: a ciência de análise de informação e o processo de construção de alfas. Desenvolve-se analiticamente a equação de Valor Adicionado (VA) mostrando que o índice Information Ratio (IR) é diretamente proporcional à quantidade de valor que se pode adicionar e, portanto, um excelente índice para comparação de estratégias. Há um capítulo destinado à definição e ao estudo do IR onde se mostra os prós e contras de sua utilização. Para que se justifique a análise de uma informação, deve haver um embasamento econômico/financeiro mínimo que mostre algum poder de previsão de retorno. Caso contrário, estaria-se desencadeando um perigoso processo de Data Mining, que pode mascarar a análise de informação fazendo parecer que existe informação onde na verdade não há. Assim, a dissertação apresenta, ainda, um capítulo destinado somente ao estudo dos principais índices financeiros utilizados pela indústria de fundos, mostrando, inclusive analiticamente, porque alguns deles são indicados para previsão de retorno.Em seguida, utilizando-se o software desenvolvido em Matlab com banco de dados em ACCESS, analisa-se todos os índices aqui estudados para o período histórico compreendido entre Jan/1998 e Dez/1999. Os resultados mostram que os índices mais populares, como o Book-to-Price, apresentam os maiores níveis de IR. Por fim, explica-se o processo de construção de alfas, que é, em última instância, o input básico para o processo de otimização de carteiras. Enfatiza-se o fenômeno de - alpha eating -, explicando-o e mostrando como evitá-lo. / [en] This dissertation presents an overview about the active portfolio management process focusing exclusively on the first two stages: the information analysis science and alpha building. The Value Added (VA) formula is analytic developed showing that the Information Ratio (IR) is directly proportional to the amount of value that a strategy can add, and therefore, is an excellent ratio for comparing different strategies. On an exclusive chapter the IR is defined and studied demonstrating the advantages and disadvantages of it s use.For an information to be analyzed there must be a minimum economic/financial background that justifies some return forecasting power.Otherwise, we could be starting a data mining process that can fool information analysis into believing that information exists when it does not. So on, this dissertation presents a chapter devoted to the study of the main financial ratios used by the asset management industry, demonstrating, even analytically, why some financial ratios can predict returns. Next, using a software developed on Matlab framework capturing data from an ACCESS database, all the financial ratios studied in this dissertation are analyzed for the period going from Jan/1998 to Dez/1999. The results obtained show that the most frequently used financial ratios, as the book-to-price ratio for example, are the ones which better perform in terms of IR.Concluding, alpha building, which is after all the basic input for portfolio optimization, is explained. The chapter emphasizes the alpha eating phenomenon explaining how it is detonated and how it can be avoided. .

Active weight, active expense ratio and active alpha are measures that can be calculated with relative ease for any fund using publicly available data. However, for active weight to be truly useful to an investor the relationship between these quantities and fund performance needed to be explored in greater detail. Furthermore, the costs of South African unit trust funds had not been studied using Miller’s techniques and needed further study. Finally, active weight had not been used to study the evolution of active management over time. Using quarterly South African unit trust fund data this study delivered on the following key findings: that funds with higher active weight provide excess returns to their investors; that funds with a higher active expense ratio do not necessarily provide greater returns; and that the active alpha for South African unit trusts is negatively correlated with fund performance. / Dissertation (MBA)--University of Pretoria, 2012. / Gordon Institute of Business Science (GIBS) / unrestricted

Recently, the debate on passive versus active fund management has been a major focus on the Swedish capital market. Passive management is gaining more and more market shares. However, theories and previous research show that Smart Beta strategies outperform their passive benchmark index. The Smart Beta strategy is described as a hybrid between active and passive fund management, where it takes advantage of the low management cost of passive fund management and active fund management’s ability to select. This study presents three new Smart Beta strategies based on the key ratios ROA, profit margin and gross margin. The purpose of the study is to investigate whether any of the three Smart Beta portfolios can perform better than the Swedish market based on OMXS30 from a risk-adjusted perspective. Previous studies have shown that Smart Beta portfolios outperform their benchmark index. However, this study's contributing key figures show no excess return for the investigated period on the Swedish stock market.