Control systems engineering
A reformulation of a mean-absolute deviation portfolio optimization model
Management Science
Investment strategies under transaction costs: the finite horizon case
Management Science
Neutral Networks in Optimization
Neutral Networks in Optimization
A Hierarchical Self-organised Classification of `Multinational' Corporations
IDEAL '08 Proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning
Expert Systems with Applications: An International Journal
A hybrid intelligent algorithm for portfolio selection problem with fuzzy returns
Journal of Computational and Applied Mathematics
Portfolio management with minimum guarantees: some modeling and optimization issues
Proceedings of the 2009 conference on Neural Nets WIRN09: Proceedings of the 19th Italian Workshop on Neural Nets, Vietri sul Mare, Salerno, Italy, May 28--30 2009
Fuzzy multi-objective portfolio selection model with transaction costs
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
A model of portfolio optimization using time adapting genetic network programming
Computers and Operations Research
Simulation model driven performance evaluation for enterprise applications
Proceedings of the 3rd International ICST Conference on Simulation Tools and Techniques
Fuzzy mean-variance-skewness portfolio selection models by interval analysis
Computers & Mathematics with Applications
Genetic relation algorithm with guided mutation for the large-scale portfolio optimization
Expert Systems with Applications: An International Journal
PB-ADVISOR: A private banking multi-investment portfolio advisor
Information Sciences: an International Journal
An approach to portfolio selection using an ARX predictor for securities' risk and return
Expert Systems with Applications: An International Journal
International Journal of Applied Evolutionary Computation
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In this study, a novel neural network-based mean-variance-skewness model for optimal portfolio selection is proposed integrating different forecasts and trading strategies, as well as investors' risk preference. Based on the Lagrange multiplier theory in optimization and the radial basis function (RBF) neural network, the model seeks to provide solutions satisfying the trade-off conditions of mean-variance-skewness. The feasibility of the RBF network-based mean-variance-skewness model is verified with a simulation experiment. The experimental results show that, for all examined investor risk preferences and investment assets, the proposed model is a fast and efficient way of solving the trade-off in the mean-variance-skewness portfolio problem. In addition, we also find that the proposed approach can also be used as an alternative tool for evaluating various forecasting models.