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We introduce a new methodology, that incorporates advanced higher moments evaluation in a new approach of the Portfolio Selection problem, supported by effective Computational Intelligence models. The Portfolio Intelligence (PI) model extracts hidden patterns out of the numerous accounting data and financial statements filtering misguiding effects such as(More)
We examine the efficiency of various Jordan Elman models either in neural or in hybrid neuro-genetic networks form to conclude on an optimal model that will be valuable in portfolio selection. The Jordan and Elman neural networks on a hybrid form of genetic algorithms optimization, in a specific topology, outperformed all the other Jordan Elman models and(More)
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