The amount of public money invested in the venture capital industry has increased sub-stantially over the last few decades. The goal is, in general, to facilitate growth in highly in-novative small and medium sized enterprises (SMEs) by securing their supply of capital in early stages. Hence, an important aspect of the effectiveness of public investment is wheth-er it increases the investees’ ability to attract additional funding. The process through which public investments can contribute to a better supply of capital to SMEs by more than just their own investment is commonly known as the catalysing or leverage effect of public in-vestment. In order to increase understanding of how this effect can be maximized, this study com-pares the amount of capital attracted to Swedish SMEs as a result of public fund-of-fund (FoF) investment to that of direct public investments. This study shows that: - FoFs are more effective in increasing the capital supply to SMEs in the market. - Public investments have a higher catalysing effect on the fund level than on the enterprise level. Hence, EUR 1 invested at the fund level has a larger positive impact for SMEs than EUR 1 invested at the enterprise level. - The investment quality of private venture capital (VC) investments is generally higher than that of direct public investments. Hence, FoFs allows public inves-tors to "free ride" on the skills of private VCs rather than setting up own struc-tures. / Masters Thesis

本篇論文主要是將Black-Litterman模型應用在組合型基金上。從一個組合型基金的基金經理人角度出發，在有限的風險下，如何進行資產配置使其達到報酬極大化的目標？第二章介紹mean-variance模型，以及其模型之缺點。第三章介紹Black-Litterman模型，其不僅可以改善mean-variace模型的缺點，此外允許投資人加入主觀看法，結合數量方法以及投資人的主觀看法是此模型的特色之一。第四章，針對兩個模型的進行比較。最後，我們發現：BLack-Litterman模型不僅符合經濟直覺，進行資產配置時也展現模型的穩定性。 / This paper applies a popular asset allocation model: the Black-Litterman model on a fund of funds. First, an overview is given of the foundations of modern portfolio theory with the mean-variance model. Next, we discuss some improvements that could be made over the mean-variance model. The Black-Litterman model addresses some of these flaws and tries to improve them. Finally, simulation has been performed to compare the performance of the Black-Litterman model to mean-variance optimization. The models have been compared in intuitiveness and stability. The conclusion can be drawn that BL-model improves the mean-variance model, in our simulation, both in intuitiveness and stability.

Thesis focuses on analysis of the possibility of drawing financial resources from EU funds for the railway infrastructure in the Czech Republic. The aim of the work is the analysis of the whole project cycle, and also the utilization of financial resources of EU funds for railway infrastructure in other countries of the European Union.

This thesis aims to investigate different types of optimization methods that can be used when optimizing fund of fund portfolios. Moreover, the thesis investigates which funds that should be included and what their respective portfolio weights should be, in order to outperform the Swedish SIX Portfolio Return Index. The funds considered for the particular fund of funds in this thesis are all managed by a particular company. The optimization frameworks applied include traditional mean variance optimization, min conditional value at risk optimization, as well as optimization methods studying alpha in combination with the risk measures tracking error and maximum drawdown, respectively. All four optimization methods were applied on a ten years data period as well as on a five years data period. It was found that while the funds have different strengths and weaknesses, four of the funds were considered most appropriate for the fund of funds. Geography and sector constraints were also taken into account and it was found that, in this particular case, the healthcare sector constraint affected the allocated portfolio weights the most. / Syftet med detta masterexamensarbete är att undersöka olika typer av optimeringsmetoder som kan användas vid optimering av en fond i fond. Vidare är syftet med optimeringen att utvärdera vilka fonder som bör inkluderas och vilka deras respektive portföljvikter bör vara för att prestera bättre än det svenska SIX Portfolio Return Indexet. Optimeringsmetoderna inkluderar traditionell modern portföljteori, minimering av conditional Value at Risk och optimeringsmetoder som studerar alpha i kombination med riskmåtten tracking error respektive maximum drawdown. Alla fyra optimeringsmetoder applicerades på en tio år lång respektive fem år lång dataperiod. Det visade sig att även om fonderna har olika styrkor och svagheter kunde fyra av fonderna anses vara mest lämpliga att inkluderas i fond i fonden. Geografiska och sektoriella begränsningar beaktades och det konstaterades att sektorbegränsningen för hälsovårdssektorn hade störst påverkan på resultatet.

Submitted by Tiago Duba (tiagoduba@gmail.com) on 2013-11-04T01:30:15Z No. of bitstreams: 1 Dissertação MFEE EGPE - Tiago Duba.pdf: 2254622 bytes, checksum: ec194772b1bfdf65d5161e3beb036d4d (MD5) / Approved for entry into archive by Vitor Souza (vitor.souza@fgv.br) on 2013-12-03T12:38:51Z (GMT) No. of bitstreams: 1 Dissertação MFEE EGPE - Tiago Duba.pdf: 2254622 bytes, checksum: ec194772b1bfdf65d5161e3beb036d4d (MD5) / Made available in DSpace on 2014-01-02T19:02:06Z (GMT). No. of bitstreams: 1 Dissertação MFEE EGPE - Tiago Duba.pdf: 2254622 bytes, checksum: ec194772b1bfdf65d5161e3beb036d4d (MD5) Previous issue date: 2013-05-05 / Despite the diversity of their strategies, the returns of hedge funds generally exhibit a positive correlation with stock index. On the other hand, distinct funds categories tend to be less correlated to each other compared to funds from the same category. The idea of diversification between funds with low correlation is discussed repeatedly in the literature. In practice, however, few portfolios allocators optimize their portfolios guided by Markowitz (1953) for example. The aim of this study is to identify the optimum asset diversification within the same category. The methodology will seek to minimize the idiosyncratic risk of the investment funds through simulations with other funds in the same category. The study contains analyzes for choosing the optimal number of assets (investment funds) in a given portfolio. These results would benefit mainly the decision making process of Wealth Managements, Investment Consulter and Private Bankers. / Apesar da diversidade de suas estratégias, os retornos dos fundos de investimentos multimercado geralmente exibem correlação positiva com índices de bolsa. Por outro lado, fundos de categorias distintas tendem a ser menos correlacionados entre si se comparados a fundos de mesma categoria. A ideia de diversificação entre fundos de baixa correlação é discutida recorrentemente pela literatura. Na prática, porém, poucos alocadores de portfólios otimizam suas carteiras através das linhas de Markowitz (1953) por exemplo. O objetivo deste estudo é buscar identificar o ponto ótimo de diversificação de ativos (fundos de investimentos) dentro de uma mesma categoria. Como metodologia, buscaremos a minimização do risco idiossincrático dos fundos de investimentos através de simulações com outros fundos de mesma categoria. O estudo contém análises para a escolha do número ideal de ativos em um dado portfólio. Esses resultados beneficiariam, principalmente, o processo decisório das empresas de Wealth Managements, das Consultorias de Investimentos e dos Private Bankers.

The research presented in this thesis addresses different aspects of dynamic portfolio construction and portfolio risk measurement. It brings the research on dynamic portfolio optimization, replicating portfolio construction, dynamic portfolio risk measurement and volatility forecast together. The overall aim of this research is threefold. First, it is aimed to examine the portfolio construction and risk measurement performance of a broad set of volatility forecast and portfolio optimization model. Second, in an effort to improve their forecast accuracy and portfolio construction performance, it is aimed to propose new models or new formulations to the available models. Third, in order to enhance the replication performance of hedge fund returns, it is aimed to introduce a replication approach that has the potential to be used in numerous applications, in investment management. In order to achieve these aims, Chapter 2 addresses risk measurement in dynamic portfolio construction. In this chapter, further evidence on the use of multivariate conditional volatility models in hedge fund risk measurement and portfolio allocation is provided by using monthly returns of hedge fund strategy indices for the period 1990 to 2009. Building on Giamouridis and Vrontos (2007), a broad set of multivariate GARCH models, as well as, the simpler exponentially weighted moving average (EWMA) estimator of RiskMetrics (1996) are considered. It is found that, while multivariate GARCH models provide some improvements in portfolio performance over static models, they are generally dominated by the EWMA model. In particular, in addition to providing a better risk-adjusted performance, the EWMA model leads to dynamic allocation strategies that have a substantially lower turnover and could therefore be expected to involve lower transaction costs. Moreover, it is shown that these results are robust across the low - volatility and high-volatility sub-periods. Chapter 3 addresses optimization in dynamic portfolio construction. In this chapter, the advantages of introducing alternative optimization frameworks over the mean-variance framework in constructing hedge fund portfolios for a fund of funds. Using monthly return data of hedge fund strategy indices for the period 1990 to 2011, the standard mean-variance approach is compared with approaches based on CVaR, CDaR and Omega, for both conservative and aggressive hedge fund investors. In order to estimate portfolio CVaR, CDaR and Omega, a semi-parametric approach is proposed, in which first the marginal density of each hedge fund index is modelled using extreme value theory and the joint density of hedge fund index returns is constructed using a copula-based approach. Then hedge fund returns from this joint density are simulated in order to compute CVaR, CDaR and Omega. The semi-parametric approach is compared with the standard, non-parametric approach, in which the quantiles of the marginal density of portfolio returns are estimated empirically and used to compute CVaR, CDaR and Omega. Two main findings are reported. The first is that CVaR-, CDaR- and Omega-based optimization offers a significant improvement in terms of risk-adjusted portfolio performance over mean-variance optimization. The second is that, for all three risk measures, semi-parametric estimation of the optimal portfolio offers a very significant improvement over non-parametric estimation. The results are robust to as the choice of target return and the estimation period. Chapter 4 searches for improvements in portfolio risk measurement by addressing volatility forecast. In this chapter, two new univariate Markov regime switching models based on intraday range are introduced. A regime switching conditional volatility model is combined with a robust measure of volatility based on intraday range, in a framework for volatility forecasting. This chapter proposes a one-factor and a two-factor model that combine useful properties of range, regime switching, nonlinear filtration, and GARCH frameworks. Any incremental improvement in the performance of volatility forecasting is searched for by employing regime switching in a conditional volatility setting with enhanced information content on true volatility. Weekly S&P500 index data for 1982-2010 is used. Models are evaluated by using a number of volatility proxies, which approximate true integrated volatility. Forecast performance of the proposed models is compared to renowned return-based and range-based models, namely EWMA of Riskmetrics, hybrid EWMA of Harris and Yilmaz (2009), GARCH of Bollerslev (1988), CARR of Chou (2005), FIGARCH of Baillie et al. (1996) and MRSGARCH of Klaassen (2002). It is found that the proposed models produce more accurate out of sample forecasts, contain more information about true volatility and exhibit similar or better performance when used for value at risk comparison. Chapter 5 searches for improvements in risk measurement for a better dynamic portfolio construction. This chapter proposes multivariate versions of one and two factor MRSACR models introduced in the fourth chapter. In these models, useful properties of regime switching models, nonlinear filtration and range-based estimator are combined with a multivariate setting, based on static and dynamic correlation estimates. In comparing the out-of-sample forecast performance of these models, eminent return and range-based volatility models are employed as benchmark models. A hedge fund portfolio construction is conducted in order to investigate the out-of-sample portfolio performance of the proposed models. Also, the out-of-sample performance of each model is tested by using a number of statistical tests. In particular, a broad range of statistical tests and loss functions are utilized in evaluating the forecast performance of the variance covariance matrix of each portfolio. It is found that, in terms statistical test results, proposed models offer significant improvements in forecasting true volatility process, and, in terms of risk and return criteria employed, proposed models perform better than benchmark models. Proposed models construct hedge fund portfolios with higher risk-adjusted returns, lower tail risks, offer superior risk-return tradeoffs and better active management ratios. However, in most cases these improvements come at the expense of higher portfolio turnover and rebalancing expenses. Chapter 6 addresses the dynamic portfolio construction for a better hedge fund return replication and proposes a new approach. In this chapter, a method for hedge fund replication is proposed that uses a factor-based model supplemented with a series of risk and return constraints that implicitly target all the moments of the hedge fund return distribution. The approach is used to replicate the monthly returns of ten broad hedge fund strategy indices, using long-only positions in ten equity, bond, foreign exchange, and commodity indices, all of which can be traded using liquid, investible instruments such as futures, options and exchange traded funds. In out-of-sample tests, proposed approach provides an improvement over the pure factor-based model, offering a closer match to both the return performance and risk characteristics of the hedge fund strategy indices.

The aim of thesis ,,Development of selected small towns with using available support programmes" is to evaluate the present situation of selected small tors and a proposal for their further development by using available support programmes. The theoretical part of the thesis is focused on explanation of all concepts of these small towns and the practical part includes a analysis of received subsidies and their total evaluation and other potential projects for the development of selected towns with using available support programmes.