7 resultados para Particle swarm optimization algorithm PSO
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Dissertation to obtain the degree of Doctor of Philosophy in Biomedical Engineering
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IEEE International Symposium on Circuits and Systems, pp. 724 – 727, Seattle, EUA
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Thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Electrical and Computer Engineering
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Dissertation presented to obtain a Ph.D. degree in Engineering and Technology Sciences, Systems Biology at the Instituto de Tecnologia QuÃmica e Biológica, Universidade Nova de Lisboa
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores
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Submitted in partial fulfillment for the Requirements for the Degree of PhD in Mathematics, in the Speciality of Statistics in the Faculdade de Ciências e Tecnologia
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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.