Given a set of available assets, the portfolio selection problem consists in finding out the best way of investing a particular amount of money in the assets. Some heuristic methods based on evolutionary algorithms, tabu search and simulated annealing have been developed in the past. Here we present a Hopfield neural network model to solve the portfolio selection problem, comparing the new results to those obtained with the other heuristic methods.
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