46 resultados para Stock return predictability


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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

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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

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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

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A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

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This paper analyzes the in-, and out-of sample, predictability of the stock market returns from Eurozone’s banking sectors, arising from bank-specific ratios and macroeconomic variables, using panel estimation techniques. In order to do that, I set an unbalanced panel of 116 banks returns, from April, 1991, to March, 2013, to constitute equal-weighted country-sorted portfolios representative of the Austrian, Belgian, Finish, French, German, Greek, Irish, Italian, Portuguese and Spanish banking sectors. I find that both earnings per share (EPS) and the ratio of total loans to total assets have in-sample predictive power over the portfolios’ monthly returns whereas, regarding the cross-section of annual returns, only EPS retain significant explanatory power. Nevertheless, the sign associated with the impact of EPS is contrarian to the results of past literature. When looking at inter-yearly horizon returns, I document in-sample predictive power arising from the ratios of provisions to net interest income, and non-interest income to net income. Regarding the out-of-sample performance of the proposed models, I find that these would only beat the portfolios’ historical mean on the month following the disclosure of year-end financial statements. Still, the evidence found is not statistically significant. Finally, in a last attempt to find significant evidence of predictability of monthly and annual returns, I use Fama and French 3-Factor and Carhart models to describe the cross-section of returns. Although in-sample the factors can significantly track Eurozone’s banking sectors’ stock market returns, they do not beat the portfolios’ historical mean when forecasting returns.

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This paper analyses the Portuguese stock market since it reopened in 1977, with a special focus on the evolution of the statistic and stochastic characteristics of the market return throughout this 36 year period. The market return for the period of time between 1977 and 2012 (September 28th) is estimated and then compared with the return that would have been achieved with Government bonds and treasury bills, which allows us to confirm that the hierarchy of return / risk across the different financial instruments is verified. The market risk premium for this 36 year period is also estimated and a comparison with other markets is performed, suggesting that the Portuguese market’s risk has not been compensated by an adequate return. The study also examines the evolution of the Portuguese market’s volatility in the 1977-2012 period and compares it with other markets, showing the existence of extremely high peaks during the first 11 years, but indicating a downwards trend throughout the whole period under analysis. Finally, the correlation between market returns for Portugal and for other countries and the degree of integration are estimated and their evolution throughout time is assessed, leading to the conclusion that the performance of the Portuguese stock market has become increasingly correlated with major European markets – correlation with some markets close to 0.70 from 2000 onwards-, but that country-specific risk factors are still relevant.

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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

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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

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Throughout the last years technologic improvements have enabled internet users to analyze and retrieve data regarding Internet searches. In several fields of study this data has been used. Some authors have been using search engine query data to forecast economic variables, to detect influenza areas or to demonstrate that it is possible to capture some patterns in stock markets indexes. In this paper one investment strategy is presented using Google Trends’ weekly query data from major global stock market indexes’ constituents. The results suggest that it is indeed possible to achieve higher Info Sharpe ratios, especially for the major European stock market indexes in comparison to those provided by a buy-and-hold strategy for the period considered.

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Dissertation submitted to the Faculty of Sciences and Technology of New University of Lisbon for obtaining the degree of Master in Environmental Management Systems

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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

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Dissertação apresentada para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Ciências da Comunicação, especialização em Comunicação e Artes

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Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

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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

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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