PORTFOLIO SELECTION AND MANAGEMENT USING A HYBRID INTELLIGENT AND STATISTICAL SYSTEM

• Autor: Lazo Lazo y Cols., Juan G.
• Formato: artículo
• Fecha de Publicación: 2019
• Institución: Centro de Preparación para la Ciencia y Tecnología
• Repositorio: ECIPERÚ
• Lenguaje: español
• OAI Identifier: oai:revistas.eciperu.net:article/141
• Enlace del recurso: https://revistas.eciperu.net/index.php/ECIPERU/article/view/141
• Nivel de acceso: acceso abierto
• Materia: Genetic Algorithms, Neural Networks, GARCH, VaR, Volatility.

This paper presents the development of a hybrid system based on Genetic Algorithms, Neural Networks and the GARCH model for the selection of stocks and the management of investment portfolios. The hybrid system comprises four modules: a genetic algorithm for selecting the assets that will form the investment portfolio, the GARCH model for forecasting stock volatility, a neural network for predicting asset returns for the portfolio, and another genetic algorithm for determining the optimal weights for each asset. Portfolio management has consisted of weekly updates over a period of 49 weeks.