Portfolio selection using neural networks

Details Portfolio selection using neural networks Portfolio selection using neural networks

2005-01-03

arxiv.org/abs/cs/0501005v1

Computers & Operations Research 34 (2007) 1177-1191

Computer Science

Neural and Evolutionary Computing

12 pages; submitted to "Computers & Operations Research"

Scientific paper

10.1016/j.cor.2005.06.017

In this paper we apply a heuristic method based on artificial neural networks in order to trace out the efficient frontier associated to the portfolio selection problem. We consider a generalization of the standard Markowitz mean-variance model which includes cardinality and bounding constraints. These constraints ensure the investment in a given number of different assets and limit the amount of capital to be invested in each asset. We present some experimental results obtained with the neural network heuristic and we compare them to those obtained with three previous heuristic methods.

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