Using Mean-Variance Model and Genetic Algorithm to Find the Optimized Weights of Portfolio of Funds - Tapa blanda

Lai, David

 
9783836492973: Using Mean-Variance Model and Genetic Algorithm to Find the Optimized Weights of Portfolio of Funds
Tapa blanda
ISBN 10: 3836492970 ISBN 13: 9783836492973
Editorial: VDM Verlag Dr. Mueller e.K., 2008

Sinopsis

This study investigates the performance of the weight optimization by comparing the performance of the portfolios of fund of funds (FoF) constructed by the Markowitz Mean-Variance (MV) model or Genetic Algorithm (GA) to that of S&P 500 and that of equal weight portfolio of Mutual funds. The chosen target funds are denominated in U.S. dollar or euros, and are chosen from the European market, United European market, Emerging market, Pacific market, South Asia market, Asia Pacific Zone market, American market, and Global market. The study period started on February 1, 1998 and ended on December 1, 2006. The Markowitz Mean-Variance model is a famous investment theory in portfolio selection problems. But Markowitz Mean-Variance model requires the assumption that the securities must follow the normal distribution. On the contrary, Genetic Algorithm is a methodology with artificial intelligence that is free of the assumption of normal distribution, and it can also be applied to the portfolio selection and optimization problems. In this thesis, we test whether the Genetic Algorithm can beat the traditional Markowitz Mean-Variance model or not.

"Sinopsis" puede pertenecer a otra edición de este libro.

Reseña del editor

This study investigates the performance of the weight optimization by comparing the performance of the portfolios of fund of funds (FoF) constructed by the Markowitz Mean-Variance (MV) model or Genetic Algorithm (GA) to that of S&P 500 and that of equal weight portfolio of Mutual funds. The chosen target funds are denominated in U.S. dollar or euros, and are chosen from the European market, United European market, Emerging market, Pacific market, South Asia market, Asia Pacific Zone market, American market, and Global market. The study period started on February 1, 1998 and ended on December 1, 2006. The Markowitz Mean-Variance model is a famous investment theory in portfolio selection problems. But Markowitz Mean-Variance model requires the assumption that the securities must follow the normal distribution. On the contrary, Genetic Algorithm is a methodology with artificial intelligence that is free of the assumption of normal distribution, and it can also be applied to the portfolio selection and optimization problems. In this thesis, we test whether the Genetic Algorithm can beat the traditional Markowitz Mean-Variance model or not.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
VDM Verlag Dr. Mueller e.K.
Año de publicación
2008
Idioma
Inglés
ISBN 10 
3836492970
ISBN 13 
9783836492973
Encuadernación
Tapa blanda
Número de páginas
72
Contacto del fabricante
no disponible
Persona responsable
no disponible