3 resultados para predictability

em Universidade do Minho


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We test the predictive ability of the transitory deviations of consumption from its common trend with aggregate wealth and labour income, cay, for both future equity and housing risk premia in emerging market economies. Using quarterly data for 31 markets, our country-level evidence shows that forecasting power of cay vis-à-vis stock returns is high for Brazil, China, Colombia, Israel, Korea, Latvia and Malaysia. As for housing returns, the empirical evidence suggests that financial and housing assets are perceived as complements in the case of Chile, Russia, South Africa and Thailand, and as substitutes in Argentina, Brazil, Hong Kong, Indonesia, Korea, Malaysia, Mexico and Taiwan. Using a panel econometric framework, we find that the cross-country heterogeneity observed in asset return predictability does not accrue to regional location, but can be attributed to differences in the degree of equity market development and in the level of income.

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Dissertação de mestrado em Engenharia e Gestão da Qualidade

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The use of genome-scale metabolic models has been rapidly increasing in fields such as metabolic engineering. An important part of a metabolic model is the biomass equation since this reaction will ultimately determine the predictive capacity of the model in terms of essentiality and flux distributions. Thus, in order to obtain a reliable metabolic model the biomass precursors and their coefficients must be as precise as possible. Ideally, determination of the biomass composition would be performed experimentally, but when no experimental data are available this is established by approximation to closely related organisms. Computational methods however, can extract some information from the genome such as amino acid and nucleotide compositions. The main objectives of this study were to compare the biomass composition of several organisms and to evaluate how biomass precursor coefficients affected the predictability of several genome-scale metabolic models by comparing predictions with experimental data in literature. For that, the biomass macromolecular composition was experimentally determined and the amino acid composition was both experimentally and computationally estimated for several organisms. Sensitivity analysis studies were also performed with the Escherichia coli iAF1260 metabolic model concerning specific growth rates and flux distributions. The results obtained suggest that the macromolecular composition is conserved among related organisms. Contrasting, experimental data for amino acid composition seem to have no similarities for related organisms. It was also observed that the impact of macromolecular composition on specific growth rates and flux distributions is larger than the impact of amino acid composition, even when data from closely related organisms are used.