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DEIM-RR-04-004 (229.8Kb)
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Title

Portfolio selection using neural networks

Author/s

Alberto Fernández, Sergio Gómez

Date

30-12-2004

Research report type

Recerca

Language

Anglés

Number of pages

12

Summary

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.

Keywords

Portfolio selection, Efficient frontier, Neural networks, Hopfield network