Determination of the world stock indices’ co-movements by association rule mining

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Purpose: This study aims to provide preliminary information to the investor by determining which indices co-movement, with the data mining method. Design/methodology/approach: In this context, data sets containing daily opening and closing prices between 2001 and 2019 have been created for 11 stock...

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Detalles Bibliográficos
Autores: Kartal, Burcu, Fatih Sert, Mehmet, Kutlu, Melih
Formato: artículo
Fecha de Publicación:2022
Institución:Universidad ESAN
Repositorio:ESAN-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.esan.edu.pe:20.500.12640/3281
Enlace del recurso:https://revistas.esan.edu.pe/index.php/jefas/article/view/632
https://hdl.handle.net/20.500.12640/3281
https://doi.org/10.1108/JEFAS-04-2020-0150
Nivel de acceso:acceso abierto
Materia:Data mining
Association rules
Stock market index
Global financial markets
Minería de datos
Reglas de asociación
Índice bursátil
Mercados financieros globales
https://purl.org/pe-repo/ocde/ford#5.02.04
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dc.title.en_EN.fl_str_mv Determination of the world stock indices’ co-movements by association rule mining
title Determination of the world stock indices’ co-movements by association rule mining
spellingShingle Determination of the world stock indices’ co-movements by association rule mining
Kartal, Burcu
Data mining
Association rules
Stock market index
Global financial markets
Minería de datos
Reglas de asociación
Índice bursátil
Mercados financieros globales
https://purl.org/pe-repo/ocde/ford#5.02.04
title_short Determination of the world stock indices’ co-movements by association rule mining
title_full Determination of the world stock indices’ co-movements by association rule mining
title_fullStr Determination of the world stock indices’ co-movements by association rule mining
title_full_unstemmed Determination of the world stock indices’ co-movements by association rule mining
title_sort Determination of the world stock indices’ co-movements by association rule mining
author Kartal, Burcu
author_facet Kartal, Burcu
Fatih Sert, Mehmet
Kutlu, Melih
author_role author
author2 Fatih Sert, Mehmet
Kutlu, Melih
author2_role author
author
dc.contributor.author.fl_str_mv Kartal, Burcu
Fatih Sert, Mehmet
Kutlu, Melih
dc.subject.en_EN.fl_str_mv Data mining
Association rules
Stock market index
Global financial markets
topic Data mining
Association rules
Stock market index
Global financial markets
Minería de datos
Reglas de asociación
Índice bursátil
Mercados financieros globales
https://purl.org/pe-repo/ocde/ford#5.02.04
dc.subject.es_ES.fl_str_mv Minería de datos
Reglas de asociación
Índice bursátil
Mercados financieros globales
dc.subject.ocde.none.fl_str_mv https://purl.org/pe-repo/ocde/ford#5.02.04
description Purpose: This study aims to provide preliminary information to the investor by determining which indices co-movement, with the data mining method. Design/methodology/approach: In this context, data sets containing daily opening and closing prices between 2001 and 2019 have been created for 11 stock market indexes in the world. The association rule algorithm, one of the data mining techniques, is used in the analysis of the data. Findings: It is observed that the US stock market indices take part in the highest confidence levels between association rules. The XU100 stock index co-movement with both the European stock market indices and the US stock indices. In addition, the Hang Seng Index (HSI) (Hong Kong) takes part in the association rules of all stock market indices. Originality/value: The important issue for data sets is that the opening/closing values of the same day or the previous day are taken into account according to the open or closed status of other stock market indices by taking the opening time of the stock exchange index to be created. Therefore, data sets are arranged for each stock market index, separately. As a result of this data set arranging process, it is possible to find out co-movements of the stock market indexes. It is proof that the world stock indices have co-movement, and this continues as a cycle.
publishDate 2022
dc.date.accessioned.none.fl_str_mv 2023-01-13T14:07:34Z
dc.date.available.none.fl_str_mv 2023-01-13T14:07:34Z
dc.date.issued.fl_str_mv 2022-12-28
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dc.identifier.none.fl_str_mv https://revistas.esan.edu.pe/index.php/jefas/article/view/632
dc.identifier.citation.none.fl_str_mv Kartal, B., Fatih Sert, M., & Kutlu, M. (2022). Determination of the world stock indices’ co-movements by association rule mining. Journal of Economics, Finance and Administrative Science, 27(54), 231–246. https://doi.org/10.1108/JEFAS-04-2020-0150
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12640/3281
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1108/JEFAS-04-2020-0150
url https://revistas.esan.edu.pe/index.php/jefas/article/view/632
https://hdl.handle.net/20.500.12640/3281
https://doi.org/10.1108/JEFAS-04-2020-0150
identifier_str_mv Kartal, B., Fatih Sert, M., & Kutlu, M. (2022). Determination of the world stock indices’ co-movements by association rule mining. Journal of Economics, Finance and Administrative Science, 27(54), 231–246. https://doi.org/10.1108/JEFAS-04-2020-0150
dc.language.none.fl_str_mv Inglés
dc.language.iso.none.fl_str_mv eng
language_invalid_str_mv Inglés
language eng
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spelling Kartal, BurcuFatih Sert, MehmetKutlu, Melih2023-01-13T14:07:34Z2023-01-13T14:07:34Z2022-12-28https://revistas.esan.edu.pe/index.php/jefas/article/view/632Kartal, B., Fatih Sert, M., & Kutlu, M. (2022). Determination of the world stock indices’ co-movements by association rule mining. Journal of Economics, Finance and Administrative Science, 27(54), 231–246. https://doi.org/10.1108/JEFAS-04-2020-0150https://hdl.handle.net/20.500.12640/3281https://doi.org/10.1108/JEFAS-04-2020-0150Purpose: This study aims to provide preliminary information to the investor by determining which indices co-movement, with the data mining method. Design/methodology/approach: In this context, data sets containing daily opening and closing prices between 2001 and 2019 have been created for 11 stock market indexes in the world. The association rule algorithm, one of the data mining techniques, is used in the analysis of the data. Findings: It is observed that the US stock market indices take part in the highest confidence levels between association rules. The XU100 stock index co-movement with both the European stock market indices and the US stock indices. In addition, the Hang Seng Index (HSI) (Hong Kong) takes part in the association rules of all stock market indices. Originality/value: The important issue for data sets is that the opening/closing values of the same day or the previous day are taken into account according to the open or closed status of other stock market indices by taking the opening time of the stock exchange index to be created. Therefore, data sets are arranged for each stock market index, separately. As a result of this data set arranging process, it is possible to find out co-movements of the stock market indexes. It is proof that the world stock indices have co-movement, and this continues as a cycle.Propósito: Este estudio tiene como objetivo brindar información preliminar al inversionista determinando qué índices co-mueven, con el método de minería de datos. Diseño/metodología/enfoque: En este contexto, se han creado conjuntos de datos que contienen precios diarios de apertura y cierre entre 2001 y 2019 para 11 índices bursátiles del mundo. En el análisis de los datos se utiliza el algoritmo de reglas de asociación, una de las técnicas de minería de datos. Hallazgos: Se observa que los índices bursátiles estadounidenses participan en los niveles de confianza más altos entre reglas de asociación. El índice bursátil XU100 se mueve conjuntamente tanto con los índices bursátiles europeos como con los índices bursátiles estadounidenses. Además, el índice Hang Seng (HSI) (Hong Kong) participa en las reglas de asociación de todos los índices bursátiles. Originalidad/valor: La cuestión importante para los conjuntos de datos es que los valores de apertura/cierre del mismo día o del día anterior se tienen en cuenta de acuerdo con el estado de apertura o cierre de otros índices bursátiles tomando la hora de apertura de la bolsa. índice que se va a crear. Por lo tanto, los conjuntos de datos se organizan para cada índice bursátil por separado. Como resultado de este proceso de organización de conjuntos de datos, es posible conocer los movimientos paralelos de los índices bursátiles. Es una prueba de que los índices bursátiles mundiales tienen co-movimiento, y esto continúa como un ciclo.application/pdfInglésengUniversidad ESAN. 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