Research report: DEIM-RR-04-004
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
