An Intelligent Model for Pairs Trading Using Genetic Algorithms.
Comput Intell Neurosci
; 2015: 939606, 2015.
Article
en En
| MEDLINE
| ID: mdl-26339236
ABSTRACT
Pairs trading is an important and challenging research area in computational finance, in which pairs of stocks are bought and sold in pair combinations for arbitrage opportunities. Traditional methods that solve this set of problems mostly rely on statistical methods such as regression. In contrast to the statistical approaches, recent advances in computational intelligence (CI) are leading to promising opportunities for solving problems in the financial applications more effectively. In this paper, we present a novel methodology for pairs trading using genetic algorithms (GA). Our results showed that the GA-based models are able to significantly outperform the benchmark and our proposed method is capable of generating robust models to tackle the dynamic characteristics in the financial application studied. Based upon the promising results obtained, we expect this GA-based method to advance the research in computational intelligence for finance and provide an effective solution to pairs trading for investment in practice.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Algoritmos
/
Inversiones en Salud
/
Modelos Genéticos
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Comput Intell Neurosci
Asunto de la revista:
INFORMATICA MEDICA
/
NEUROLOGIA
Año:
2015
Tipo del documento:
Article
País de afiliación:
Taiwán