Autor según el artículo: Akyildirim, Erdinc; Bariviera, Aurelio F.; Duc Khuong Nguyen; Sensoy, Ahmet;
Departamento: Gestió d'Empreses
Autor/es de la URV: Fernández Bariviera, Aurelio
Palabras clave: Stock market Prediction Machine learning Index Forecasting Artificial neural-networks Algorithmic trading
Resumen: We compare the performance of various advanced forecasting techniques, namely artificial neural networks, k-nearest neighbors, logistic regression, Naive Bayes, random forest classifier, support vector machine, and extreme gradient boosting classifier to predict stock price movements based on past prices. We apply these methods with the high frequency data of 27 blue-chip stocks traded in the Istanbul Stock Exchange. Our findings reveal that among the selected methodologies, random forest and support vector machine are able to capture both future price directions and percentage changes at a satisfactory level. Moreover, consistent ranking of the methodologies across different time frequencies and train/test set partitions prove the robustness of our empirical findings.
Áreas temáticas: Saúde coletiva Operations research & management science Medicina i Matemática / probabilidade e estatística Management science and operations research Interdisciplinar General decision sciences Ensino Engenharias iv Engenharias iii Engenharias i Economia Decision sciences (miscellaneous) Decision sciences (all) Ciencias sociales Ciências agrárias i Ciência da computação Administração, ciências contábeis e turismo Administração pública e de empresas, ciências contábeis e turismo
Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
Direcció de correo del autor: aurelio.fernandez@urv.cat
Identificador del autor: 0000-0003-1014-1010
Fecha de alta del registro: 2024-09-07
Versión del articulo depositado: info:eu-repo/semantics/acceptedVersion
Enlace a la fuente original: https://link.springer.com/article/10.1007/s10479-021-04464-8
URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
Referencia al articulo segun fuente origial: Annals Of Operations Research. 313 (2): 639-690
Referencia de l'ítem segons les normes APA: Akyildirim, Erdinc; Bariviera, Aurelio F.; Duc Khuong Nguyen; Sensoy, Ahmet; (2022). Forecasting high-frequency stock returns: a comparison of alternative methods. Annals Of Operations Research, 313(2), 639-690. DOI: 10.1007/s10479-021-04464-8
DOI del artículo: 10.1007/s10479-021-04464-8
Entidad: Universitat Rovira i Virgili
Año de publicación de la revista: 2022
Tipo de publicación: Journal Publications
Repositori URV