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

Abstract

PurposeThis 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.FindingsIt 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/valueThe 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.

Emtia Piyasalarının Birlikte Hareketlerinin Veri Madenciliği ile İncelenmesi

“…Karaatlı et al (2021) stated that in order to create a portfolio, shares in the BIST 30 index are included in macroeconomic variables (M1 money supply, gold ounce price, export-import coverage ratio, industrial production index, foreign exchange basket, manufacturing industry capacity utilization rate, interest, producer price index, financial FP-Growth algorithm was used to analyze its movement with services confidence index, international direct investments, crude oil, S&P 500 index). In their study, Kartal et. al.…”

Comparing Decision Trees and Association Rules for Stock Market Expectations in BIST100 and BIST30

“…As another promising data science technique, association rule mining can also be used for making decisions in financial institutions (Pawar et al, 2019;Chen et al, 2022;Kartal et al, 2022). The association rule mining aims to discover a pattern of frequently used items appearing together in data sets.…”

Editorial: Journal aim and scope and ongoing positioning

“…For their part, Kartal et al (2022) demonstrated that the world stock indices have co-movement, and this continues as a cycle. Likewise, to make the right investment decision, investors must consider market mobility to form financial markets resistant to economic shocks.…”