961 resultados para PORTFOLIO INVESTMENT
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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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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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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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NSBE - UNL
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In this paper we investigate what drives the prices of Portuguese contemporary art at auction and explore the potential of art as an asset. Based on a hedonic prices model we construct an Art Price Index as a proxy for the Portuguese contemporary art market over the period of 1994 to 2014. A performance analysis suggests that art underperforms the S&P500 but overperforms the Portuguese stock market and American Government bonds. However, It does it at the cost of higher risk. Results also show that art as low correlation with financial markets, evidencing some potential in risk mitigation when added to traditional equity portfolios.
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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 and Maastricht University School of Business and Economics
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There is a growing interest in social impact assessment across the private, the public and the nonprofit sector. However, there is still limited academic research produced in this area, particularly in what concerns to the application of the Social Return of Investment (SROI) methodology. The goal of this Work Project is to give an overview of the social impact measurement literature and apply the Social Return on Investment, a flagship methodology to measure impact, to the specific case of the Social Innovation Hub (SIH). The findings suggest that each 1€ invested on the SIH generates 1,21€ in terms of social value. While this value seems very appealing to use, there are some risks in monetizing impact in such way, mainly due to the lack of reliable data available for benchmarking purposes.
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Field lab: Nova Student Portfolio
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Portfolio diversification benefits have been extensively documented and acknowledge in the literature since 1952. However, the majority of the studies have focus on an equity context, and only very few on bonds. The study purposed tries to understand and measure the diversification benefits for a pure bond portfolio by investing in securities with different credit risks, maturities and even geographies. Diversification benefits were achieved under the proposed model and some conclusions were withdrawn.
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Since the financial crisis, risk based portfolio allocations have gained a great deal in popularity. This increase in popularity is primarily due to the fact that they make no assumptions as to the expected return of the assets in the portfolio. These portfolios implicitly put risk management at the heart of asset allocation and thus their recent appeal. This paper will serve as a comparison of four well-known risk based portfolio allocation methods; minimum variance, maximum diversification, inverse volatility and equally weighted risk contribution. Empirical backtests will be performed throughout rising interest rate periods from 1953 to 2015. Additionally, I will compare these portfolios to more simple allocation methods, such as equally weighted and a 60/40 asset-allocation mix. This paper will help to answer the question if these portfolios can survive in a rising interest rate environment.
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Dissertação de mestrado em Finanças