Genetic optimization of a trading algorithm based on pattern recognition
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Fecha
2019-11
Autores
Ruiz-Cruz, Riemann
Sedano, Chelsie
Flores, Oscar
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Editor
IEEE
Resumen
Descripción
In the present paper, a trading strategy based onpattern recognition is optimized by means of a genetic algorithm.The genetic algorithm is used to determine decisions of buy/sellbased on the patterns found through time for a portfolio in thestock market. The predominant algorithms used in this workwere theK-means clustering algorithm to find the patterns indifferent time lapses, and the genetic algorithm for optimization.The results are supported by simulations using a selected sharesof the Mexican stock market.
Palabras clave
Genetic algorithm, Portfolio optimization, Trading algorithm
Citación
R. Ruiz-Cruz, C. Sedano and O. Flores. Genetic optimization of a trading algorithm based on pattern recognition. 2019 IEEE Latin American Conference on Computational Intelligence (LA-CCI), Guayaquil, Ecuador, 2019, pp. 1-6, doi: 10.1109/LA-CCI47412.2019.9037052.