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


Kartal B., Sert M. F., Kutlu M.

JOURNAL OF ECONOMICS, FINANCE AND ADMINISTRATIVE SCIENCE, pp.1-17, 2022 (Scopus) identifier

  • Publication Type: Article / Article
  • Publication Date: 2022
  • Doi Number: 10.1108/jefas-04-2020-0150
  • Journal Name: JOURNAL OF ECONOMICS, FINANCE AND ADMINISTRATIVE SCIENCE
  • Journal Indexes: Scopus, Academic Search Premier, Fuente Academica Plus, International Bibliography of Social Sciences, Business Source Elite, Business Source Premier, EconLit, Directory of Open Access Journals
  • Page Numbers: pp.1-17
  • Recep Tayyip Erdoğan University Affiliated: Yes

Abstract

Purpose This study aims to provide preliminary information to the investor by determining which indices co-movement, with the data mining method.Design/methodology/approachIn 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.