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Authors:
S. Peker, Yasar University (Izmir, Turkey) B. Aktan, University of Bahrain, Kingdom of Bahrain & Future University in Egypt (New Cairo, Egypt) M. Tvaronavičienė, Vilnius Gediminas Technical University (Vilnius, Lithuania)
Pages: 300-310
Language: English
DOI: https://doi.org/10.21272/mmi.2017.1-27
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Abstract
The aim of the article. Investment in stock market requires taking risk. Investors typically buy several stocks to create a portfolio which targets to maximize the return while keeping a certain level of risk. In today’s information-rich financial markets, one of the main challenges for individual investors in particular is to allocate the scarce sources appropriately within the wide range of investment alternatives that grouping the multiple assets based on their similar characteristics would be useful to take it out. In this paper, stock markets of the Group of 7 (G-7) countries consisting of France, United Kingdom, Germany, Italy, United States, Canada and Japan are examined over the period of 2011 and 2016 and some hierarchical clustering methods are applied on key indices namely, CAC 40 (France), FTSE 100 (UK), DAX (Germany), FTSE MIB (Italy), S&P TSX Composite (Canada), S&P 500 (USA), NIKKEI 225 (Japan) to identify the groups based on risk and return characteristics.
The results of the analysis. Cluster analysis is an innovative and a very useful method to help make sense of data. In this paper, we investigated the Group of 7’s stock markets over the period of 2011 and 2016. The single linkage, complete linkage, average linkage, centroid and Ward’s hierarchical clustering methods are performed on widely followed stock market indices namely, CAC 40 (France), FTSE 100 (UK), DAX (Germany), FTSE MIB (Italy), S&P TSX Composite (Canada), S&P 500 (USA), NIKKEI 225 (Japan) to identify the groups based on risk and return characteristics.
Conclusions and directions of further researches. Although, the differences exist at some stages, the all performed dendrograms, in this study, demonstrated that CAC 40 is merged with DAX whereas S&P 500 is merged with S&P/TSK Composite at the first stages. At the last stage, NIKKEI 225 is merged with the group of CAC 40, DAX, FTSE 100, S&P 500, S&P/TSK Composite and FTSE MIB for the studied period. Additionally, the k-means clustering is performed on means and standard deviations of daily returns. The analysis showed that CAC 40, DAX and NIKKEI 225 form a group; FTSE 100, S&P 500 and S&P TSK Composite form another group, and finally FTSE MIB itself form a group during the examined period. When twostep clustering is performed for k=3, CAC 40 and FTSE MIB form one group; DAX, NIKKEI 225 and S&P 500 form another group, and FTSE 100 and S&P TSK Composite form the third group for the related period. Results partly showed similarity by the study of [8] since the dendrograms which was obtained through the average linkage method.
Keywords: G-7 countries, hierarchical clustering, k-means, twostep clustering, stock market, innovative approach
JEL Classification: C10, F33, O31.
Cite as: Peker, S., Aktan B. & Tvaronavičienė, M. (2017). Clustering in key G-7 stock market indices: an innovative approach. Marketing and Management of Innovations, 1, 300-310. https://doi.org/10.21272/mmi.2017.1-27
This work is licensed under a Creative Commons Attribution 4.0 International License
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