PORTFOLIO SELECTION AND MANAGEMENT USING A HYBRID INTELLIGENT AND STATISTICAL SYSTEM

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 i...

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Detalles Bibliográficos
Autor: Lazo Lazo y Cols., Juan G.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2019
País:Perú
Institución:Centro de Preparación para la Ciencia y Tecnología
Repositorio:ECIPERÚ
Idioma:español
OAI Identifier:oai:revistas.eciperu.net:article/141
Acceso en línea:https://revistas.eciperu.net/index.php/ECIPERU/article/view/141
Access Level:acceso abierto
Palabra clave:Genetic Algorithms, Neural Networks, GARCH, VaR, Volatility.
Descripción
Sumario: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.

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