132 resultados para market portfolio
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The report addresses the question of what are the preferences of broadband consumers on the Portuguese telecommunication market. A triple play bundle is being investigated. The discrete choice analysis, adopted in the study, base on 110 responses, mainly from NOVA students. The data for the analysis was collected via manually designed on-line survey. The results show that the price attribute is relatively the most important one while the television attribute is being overlooked in the decision making process. Main effects examined in the research are robust. In addition, "extras" components are being tested in terms of users' preferences.
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What role do social networks play in determining migrant labor market outcomes? We examine this question using data from a random sample of 1500 immigrants living in Ireland. We propose a theoretical model formally predicting that immigrants with more contacts have additional access to job offers, and are therefore better able to become employed and choose higher paid jobs. Our empirical analysis confirms these findings, while focusing more generally on the relationship between migrants’ social networks and a variety of labor market outcomes (namely wages, employment, occupational choice and job security), contrary to the literature. We find evidence that having one more contact in the network is associated with an increase of 11pp in the probability of being employed and with an increase of about 100 euros in the average salary. However, our data is not suggestive of a network size effect on occupational choice and job security. Our findings are robust to sample selection and other endogeneity concerns.
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Field lab: Nova Student Portfolio
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This thesis does not set out to focus on the dynamics relationship between Twitter and stock prices, but instead tries to understand if using relevant information extracted from tweets has the power to increase investors’ stock picking ability, and generate alpha in portfolio’s choice relative to a benchmark. Despite the short period analyzed, it gives promising results that the sentiment analysis performed by Social Market Analytics Inc. applied to an equity portfolio, is able to generate positive abnormal returns, statistically significant in and out of sample.
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The recent financial crisis has drawn the attention of researchers and regulators to the importance of liquidity for stock market stability and efficiency. The ability of market-makers and investors to provide liquidity is constrained by the willingness of financial institutions to supply funding capital. This paper sheds light on the liquidity linkages between the Central Bank, Monetary Financial Institutions and market-makers as crucial elements to the well-functioning of markets. Results suggest the existence of causality between credit conditions and stock market liquidity for the Eurozone between 2003 and 2015. Similar evidence is found for the UK during the post-crisis period. Keywords: stock
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This paper presents an application of an Artificial Neural Network (ANN) to the prediction of stock market direction in the US. Using a multilayer perceptron neural network and a backpropagation algorithm for the training process, the model aims at learning the hidden patterns in the daily movement of the S&P500 to correctly identify if the market will be in a Trend Following or Mean Reversion behavior. The ANN is able to produce a successful investment strategy which outperforms the buy and hold strategy, but presents instability in its overall results which compromises its practical application in real life investment decisions.
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Flow of new information is what produces price changes, understanding if the market is unbalanced is fundamental to know how much inventory market makers should keep during an important economic release. After identifying which economic indicators impact the S&P and 10 year Treasuries. The Volume Synchronized Probability of Information-Based Trading (VPIN) will be used as a predictability measure. The results point to some predictability power over economic surprises of the VPIN metric, mainly when calculated using the S&P. This finding appears to be supported when analysing depth imbalance before economic releases. Inferior results were achieved when using treasuries. The final aim of this study is to fill the gap between microstructural changes and macroeconomic events.
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This study aims to replicate Apple’s stock market movement by modeling major investment profiles and investors. The present model recreates a live exchange to forecast any predictability in stock price variation, knowing how investors act when it concerns investment decisions. This methodology is particularly relevant if, just by observing historical prices and knowing the tendencies in other players’ behavior, risk-adjusted profits can be made. Empirical research made in the academia shows that abnormal returns are hardly consistent without a clear idea of who is in the market in a given moment and the correspondent market shares. Therefore, even when knowing investors’ individual investment profiles, it is not clear how they affect aggregate markets.
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This paper analyzes the Nova Student Portfolio (NSP) with the objective to understand performances of the fund. Each investment style has been analyzed (growth, value and momentum) in order to highlight what style allocation contributed positively and which had a negative impact. The results show that the team mainly invested in value stocks, which contributed positively but that its growth investments had a negative impact on the stock picking performance. The stock selection shows a major influence of the value investment style. A statistical approach shows that the market factor was the one explaining the most the NSP returns.
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This paper studies the changes in European stock market indexes composition from 1995 to 2015. It was found that there are mixed price effects producing abnormal returns around the effective replacement of added and deleted stocks. The price pressure hypothesis seems to hold for added stocks in some indexes but not for deleted stocks as there is not a clear inversion of behaviour after the replacement. Finally, the building and back testing of a trading strategy aiming to capture some of those abnormal returns shows it yields a Sharpe Ratio of 1.4 and generates an annualised alpha of 11%.
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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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Despite the extensive literature in finding new models to replace the Markowitz model or trying to increase the accuracy of its input estimations, there is less studies about the impact on the results of using different optimization algorithms. This paper aims to add some research to this field by comparing the performance of two optimization algorithms in drawing the Markowitz Efficient Frontier and in real world investment strategies. Second order cone programming is a faster algorithm, appears to be more efficient, but is impossible to assert which algorithm is better. Quadratic Programming often shows superior performance in real investment strategies.
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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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Field lab: Consulting lab
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We investigate the cointegration between VIX and CDS indices, and the possibility of exploiting it in an existing credit market timing investment model. We find cointegration over most of the sample period and the leadership of VIX over the CDS in the price discovery process. We present two methods for including cointegration into the model. Both strategies improve the in-sample and out-of-sample model performances, even though out-of-sample results are weaker. We find that in-sample better performances are explained by a stronger cointegration, concluding that in the presence of cointegration our strategies can be profitable in an investment model that considers transaction costs.