849 resultados para Stock


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In the 19th century, firms operating in the Anglo-Indian tea trade were organised using a variety ownership forms including the partnership, joint-stock and a combination of the two known as the Managing agency. Faced with both an increasing need for fixed capital and high agency costs caused by the distance between owners and managers, the firms adapted and increasingly adopted the hybrid managing agency model to overcome these problems. Using new data from Calcutta and Bengal Commercial Registers and detailed case studies of the Assam Company and Gillanders, Arbuthnot and Co, this paper demonstrates that British entrepreneurs did not see the choice of ownership as a dichotomy or firm boundaries as fixed, but instead innovatively drew on the strengths of different forms of ownership to compete and grow successfully.

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There is no consensus in the literature as to which stock characteristic best explains returns. In this study, we employ a novel econometric approach better suited than the traditional characteristic sorting method to answer this question for the UK market. We evaluate the relative explanatory power of market, size, momentum, volatility, liquidity and book-to-market factors in a semiparametric characteristic-based factor model which does not require constructing characteristic portfolios. We find that momentum is the most important factor and liquidity is the least important based on their relative contribution to the fit of the model and the proportion of sample months for which factor returns are significant. Overall, this study provides strong evidence to support that the momentum characteristic can best explain stock returns in the UK market. The econometric approach employed in this study is a novel way to assess relevant investment risk in international financial markets outside U.S. Moreover, multinational institutions and investors can use this approach to identify regional factors in order to diversify their portfolios.

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This paper uses a novel identification strategy to test the influence of news media on the stock market. Because the stock market does not impact the media coverage of the housing market, a relationship between real-estate news and shares of companies engaged in the housing market is attributable media influence. I find that the content of reporting exhibits a significant relationship with stock returns, and the amount of news with the number of trades. These relationships exist even after controlling for known risk factors, housing market performance and intra-week correlation. This finding is consistent with the function of the media as a source of information and sentiment in financial markets.

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By testing a simple asset pricing model of heterogeneous agents to characterize the power-law behavior of the DAX 30 from 1975 to 2007, we provide supporting evidence on empirical findings that investors and fund managers use combinations of fixed and switching strategies based on fundamental and technical analysis when making investment decisions. By conducting econometric analysis via Monte Carlo simulations, we show that the autocorrelation patterns, the estimates of the power-law decay indices, (FI)GARCH parameters, and tail index of the model match closely the corresponding estimates for the DAX 30. A mechanism analysis based on the calibrated model provides further insights into the explanatory power of heterogeneous agent models.

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Tese dout., Ciências e Tecnologias das Pescas, Universidade do Algarve, 2007

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Future changes in population exposures to ambient air pollution are inherently linked with long-term trends in outdoor air quality, but also with changes in the building stock. Moreover, the burden of disease is further driven by the ageing of the European populations. This study aims to assess the impact of changes in climate, emissions, building stocks and population on air pollution related human health impacts across Europe in the future. Therefore an integrated assessment model combining atmospheric models and health impacts has been setup for projections of the future developments in air pollution related premature mortality. The focus is here on the regional scale impacts of exposure to surface ozone (O3), Secondary Inorganic Aerosols (SIA) and primary particulate matter (PPM).

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A structural vector autoregressive model is employed to investigate the impact of monetary policy and real exchange rate shocks on the stock market performance of Kuwait, Oman, Saudi Arabia, Egypt and Jordan. In order to identify the structural shocks both short run and long run restrictions are applied. Unlike previous literature the contemporaneous interdependence between the financial variables are left unrestricted to give a more accurate depiction of the relationships. The heterogeneity of the results reflect the different monetary policy frameworks and stock market characteristics of these countries. Mainly, monetary policy and the real exchange rate shocks have a significant short run impact on the stock prices of the countries that apply a relatively more independent monetary policy and flexible exchange rates.

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Consumer confidence indices (CCIs) are a closely monitored barometer of countries’ economic health and an informative forecasting tool. Using European and US data, we provide a case study of the two recent stock market meltdowns (the post-dotcom bubble correction of 2000–2002 and the 2007–2009 decline at the beginning of the financial crisis) to contribute to the discussion on their appropriateness as proxies for stock markets’ investor sentiment. Investor sentiment should positively covary with stock market movements (DeLong, Shleifer, Summers, and Waldmann 1990); however, we find that the CCI–stock market relationship is not universally positive.We also do not find support for the information effect documented in the previous literature, but identify a more subtle relationship between consumer expectations about future household finances and stock market fluctuations.

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This paper provides an empirical study to assess the forecasting performance of a wide range of models for predicting volatility and VaR in the Madrid Stock Exchange. The models performance was measured by using different loss functions and criteria. The results show that FIAPARCH processes capture and forecast more accurately the dynamics of IBEX-35 returns volatility. It is also observed that assuming a heavy-tailed distribution does not improve models ability for predicting volatility. However, when the aim is forecasting VaR, we find evidence of that the Student’s t FIAPARCH outperforms the models it nests the lower the target quantile.

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Orientadora: Mestre Cláudia Maria Ferreira Pereira Lopes

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We propose a graphical method to visualize possible time-varying correlations between fifteen stock market values. The method is useful for observing stable or emerging clusters of stock markets with similar behaviour. The graphs, originated from applying multidimensional scaling techniques (MDS), may also guide the construction of multivariate econometric models.

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The goal of this study is the analysis of the dynamical properties of financial data series from worldwide stock market indices. We analyze the Dow Jones Industrial Average ( ∧ DJI) and the NASDAQ Composite ( ∧ IXIC) indexes at a daily time horizon. The methods and algorithms that have been explored for description of physical phenomena become an effective background, and even inspiration, for very productive methods used in the analysis of economical data. We start by applying the classical concepts of signal analysis, Fourier transform, and methods of fractional calculus. In a second phase we adopt a pseudo phase plane approach.

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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 Economics from the NOVA – School of Business and Economics