Optimización de portafolio con cardinalidad usando algoritmos genéticos de población dual
Portfolio optimization with cardinality using dual population genetic algorithms
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En algunos estudios se ha encontrado que, muchas veces, los algoritmos genéticos con una sola población para la solución de la optimización de portafolio con cardinalidad convergen lentamente y no obtienen los mejores resultados. Una manera de mejorar el desempeño de estos algoritmos ha sido incorporar una población adicional que actúe como buscador de máximos y mínimos locales; de esta manera, se aumenta la probabilidad de encontrar el óptimo global de la solución en un menor tiempo.
Este documento busca identificar el rendimiento en muestra y fuera de muestra de un portafolio de activos de renta variable con restricciones de cardinalidad usando algoritmos genéticos con una sola población y con población doble, estableciendo como universo el índice Dow Jones. Los resultados muestran que el desempeño puede verse afectado por los parámetros seleccionados para realizar la optimización, por lo que es importante tener en cuenta el error en la estimación de la media y la varianza del portafolio.
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