10 resultados para investment models

em CiencIPCA - Instituto Politécnico do Cávado e do Ave, Portugal


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The purpose of this research is fourfold. First, to investigate whether the determinants of international equity investment differ between investors with different degrees of information, experience and sophistication. For this purpose, the determinants of international equity investment of institutional and noninstitutional investors from 20 OECD countries, in the period 2001-2009, were analysed and compared. The results show that there are significant differences in the determinants of international equity investment between institutional and noninstitutional investors. Particularly, noninstitutional investors exhibit a more pronounced preference for equities of geographical nearby, contiguous and more transparent countries than institutional investors, suggesting that the effect of information costs and familiarity on international equity investment is stronger for less informed, experienced and sophisticated investors. Moreover, the preference for more developed equity markets and the contrarian behaviour are more severe for noninstitutional investors. Hence, the heterogeneity of institutional and noninstitutional investors in international equity investment is not negligible and therefore should be taken into account. Second, to investigate whether the determinants of international bond investment differ between investors with different degrees of information, experience and sophistication. For this purpose, the determinants of international bond investment of institutional and noninstitutional investors from 20 OECD countries, in the period 2001-2009, were analysed and compared. The results show that there are few significant differences in the determinants of international bond investment between institutional and noninstitutional investors. Particularly, the preference for bonds of more transparent countries and the return chasing behaviour are more pronounced for noninstitutional investors, whereas the preference for bonds with lower risk diversification potential is more pronounced for institutional investors. Hence, not only the results for international bond investment do not allow to support (or reject) the argument that information costs and familiarity are more important for less informed, experienced and sophisticated investors, but also they are contrary to the idea that financial variables, namely return and risk diversification, are more important for more informed, experienced and sophisticated investors. Third, to investigate whether the determinants of international equity investment differ from the determinants of international bond investment. For this purpose, the determinants of both international equity and bond investment of institutional and noninstitutional investors from 20 OECD countries, in the period 2001-2009, were analysed and compared. The results show that, although the effect of information costs on international equity investment tends to be stronger than on international bond investment, the differences between assets are not usually statistically significant, especially when the influence of financial variables is taken into account. Hence, it is not possible to conclude that international equity investment is much more information intensive than international bond investment, as suggested by Gehrig (1993) and Portes, Rey and Oh (2001), among others. Fourth, to investigate whether the flight to quality phenomenon is also observable in international investment and whether the flight to quality phenomenon is more pronounced for more sophisticated than for less sophisticated investors. For this purpose, a two-factor and three-factor ANOVA models, respectively, were applied to the international equity and bond investment of institutional and noninstitutional investors from 20 OECD countries in the period 2001-2009. The results suggest that the flight to quality phenomenon is also observable in international investment, as a change from business cycle of expansion to recession causes investors to significantly decrease the average weight invested in more risky assets (equities) and increase the average weight invested in less risky assets (bonds). The results also show that the variation on the average weight assigned to each type of asset, due to changes in business cycles, is significantly stronger for institutional investors than for noninstitutional investors, thereby suggesting that the flight to quality phenomenon is more pronounced for more sophisticated than for less sophisticated investors.

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Globalization creates new opportunities for firms to invest abroad and many economies are making active efforts to attract Foreign Direct Investment (FDI) in order to promote economic growth. Decisions to invest abroad depend on a complex set of factors, but the least corrupt countries may attract more foreign direct investment because they provide a more favorable climate for investors. In this paper we investigate the impact of corruption on FDI inflows in 73 countries, over the period 1998-2008. Our results suggest that countries where corruption is lower, the FDI inflows are greater, and so controlling corruption may be an important strategy for increase FDI inflows.

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This paper examines the performance of Portuguese equity funds investing in the domestic and in the European Union market, using several unconditional and conditional multi-factor models. In terms of overall performance, we find that National funds are neutral performers, while European Union funds under-perform the market significantly. These results do not seem to be a consequence of management fees. Overall, our findings are supportive of the robustness of conditional multi-factor models. In fact, Portuguese equity funds seem to be relatively more exposed to smallcaps and more value-oriented. Also, they present strong evidence of time-varying betas and, in the case of the European Union funds, of time-varying alphas too. Finally, in terms of market timing, our tests suggest that mutual fund managers in our sample do not exhibit any market timing abilities. Nevertheless, we find some evidence of timevarying conditional market timing abilities but only at the individual fund level.

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Abstract. Interest in design and development of graphical user interface (GUIs) is growing in the last few years. However, correctness of GUI's code is essential to the correct execution of the overall software. Models can help in the evaluation of interactive applications by allowing designers to concentrate on its more important aspects. This paper describes our approach to reverse engineering abstract GUI models directly from the Java/Swing code.

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Color model representation allows characterizing in a quantitative manner, any defined color spectrum of visible light, i.e. with a wavelength between 400nm and 700nm. To accomplish that, each model, or color space, is associated with a function that allows mapping the spectral power distribution of the visible electromagnetic radiation, in a space defined by a set of discrete values that quantify the color components composing the model. Some color spaces are sensitive to changes in lighting conditions. Others assure the preservation of certain chromatic features, remaining immune to these changes. Therefore, it becomes necessary to identify the strengths and weaknesses of each model in order to justify the adoption of color spaces in image processing and analysis techniques. This chapter will address the topic of digital imaging, main standards and formats. Next we will set the mathematical model of the image acquisition sensor response, which enables assessment of the various color spaces, with the aim of determining their invariance to illumination changes.

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Current software development relies increasingly on non-trivial coordination logic for com- bining autonomous services often running on di erent platforms. As a rule, however, in typical non-trivial software systems, such a coordination layer is strongly weaved within the application at source code level. Therefore, its precise identi cation becomes a major methodological (and technical) problem which cannot be overestimated along any program understanding or refactoring process. Open access to source code, as granted in OSS certi cation, provides an opportunity for the devel- opment of methods and technologies to extract, from source code, the relevant coordination information. This paper is a step in this direction, combining a number of program analysis techniques to automatically recover coordination information from legacy code. Such information is then expressed as a model in Orc, a general purpose orchestration language

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This paper analyses the performance and investment styles of internationally oriented Socially Responsible Investment (SRI)funds, domiciled in eight European markets, in comparison with characteristics-matched conventional funds. To the best of our knowledge, this is the first multi-country study, focused on international SRI funds (investing in Global and in European equities), to combine the matched-pairs approach with the use of robust conditional multi-factor performance evaluation models, which allow for both time-varying alphas and betas and also control for home biases and spurious regression biases.In general, the results show that differences in the performance of international SRI funds and their conventional peers are not statistically significant. Regarding investment styles, SRI and conventional funds exhibit similar factor exposures in most cases. In addition,conventional benchmarks present a higher explaining power of SRI fund returns than SRI benchmarks. Our results also show significant differences in the investment styles of SRI funds according to whether they use “best-in-class” screening strategies or not. When compared to SRI funds that employ simple negative and/or positive screens, SRI “best-in-class” funds present significantly lower exposures to small caps and momentum strategies and significantly higher exposures to local stocks.

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A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

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In this paper we investigate whether the determinants of international equity investment differ between investors with different degrees of sophistication. For this purpose, we analyse and compare the determinants of international equity investment of institutional and noninstitutional investors from 20 OECD countries (US not included) in the period 2001-2009. The results show that there are significant differences in the determinants of international equity investment between institutional and noninstitutional investors. In particular, noninstitutional investors tend to exhibit a more pronounced preference for equities of geographical nearby, contiguous and more transparent countries than institutional investors. The preference for more developed equity markets and the contrarian behaviour are also significantly more pronounced for noninstitutional than for institutional investors. These results support the argument that international equity investment of less sophisticated investors is more affected by information costs and familiarity than that of more sophisticated investors. Moreover, business cycles exert an influence on international equity investment decisions of both institutional and noninstitutional investors.

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A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.