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Article
Publication date: 5 April 2022

Burcu Kartal, Mehmet Fatih Sert and Melih Kutlu

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

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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/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.

Details

Journal of Economics, Finance and Administrative Science, vol. 27 no. 54
Type: Research Article
ISSN: 2218-0648

Keywords

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Article
Publication date: 6 October 2020

Melih Kutlu and Aykut Karakaya

This study aimed to investigate return and volatility spillover between the Borsa Istanbul (BIST) and the Moscow Stock Exchange (RTS).

243

Abstract

Purpose

This study aimed to investigate return and volatility spillover between the Borsa Istanbul (BIST) and the Moscow Stock Exchange (RTS).

Design/methodology/approach

This study used generalized autoregressive conditionally heteroscedasticity (GARCH) model for volatility and the Aggregate Shock (AS) model for return and volatility spillover. The data are divided into six sub-periods. Period events take place between Turkey and Russia.

Findings

BIST investors considered the return and volatility of the RTS, it is observed that Moscow Stock Exchange investors considered only the return of BIST at the full sample. It is only a return spillover from BIST to RTS and neither the return nor the volatility of the RTS is spillover to BIST in the pre-crisis period. No evidence of return and volatility spillover between the BIST and the RTS in the post-crisis period. The returns and volatility spillovers between Russia and Turkey are mutual feedback in the jet crisis period.

Practical implications

Economic developments between Turkey and Russia is growing rapidly in recent years. The return and volatility analysis between the stock exchanges of these two countries is important for investment decisions.

Originality/value

There are many studies in the literature about emerging markets. There are also Turkish and Russian stock exchanges in these studies. However, this study only examined return and volatility spillover analysis between the Turkish and Russian stock exchanges and prevents the results from being overlooked among other countries.

Details

Journal of Economic and Administrative Sciences, vol. 37 no. 4
Type: Research Article
ISSN: 2054-6238

Keywords

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