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Journals / Hacettepe Journal of Mathematics and Statistics / 2018 / Cilt: 47 - Sayı: 4

Hierarchies in communities of Borsa Istanbul Stock Exchange

Mehmet Ali BALCI
Pages
921–936
Publication Date
2022-10-18
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results suggest that the approach is demonstrably effective for Borsa Istanbul sessionally data returns.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Nowadays, increase of the analyzing stock markets as complex systems lead graph theory to play key role.
📊
Key Findings & Data:For instance detecting graph communities is an important task in the analysis of stocks, and minimum spanning trees let us to get important information for the topology of the market.
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Conclusion & Impact:The results suggest that the approach is demonstrably effective for Borsa Istanbul sessionally data returns.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Financial networks · Graph communities · Hierarchy structures

Abstract

Nowadays, increase of the analyzing stock markets as complex systems lead graph theory to play key role. For instance detecting graph communities is an important task in the analysis of stocks, and minimum spanning trees let us to get important information for the topology of the market. In this paper, we introduce a method to build a connected graph representation of Borsa Istanbul based on the spectrum. We, then, detect graph communities and internal hierarchies by using the minimum spanning trees. The results suggest that the approach is demonstrably effective for Borsa Istanbul sessionally data returns.

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Cite This Article

BALCI, M. A. (2022). Hierarchies in communities of Borsa Istanbul Stock Exchange. Hacettepe Journal of Mathematics and Statistics, Cilt: 47 - Sayı: 4, 921–936. https://ajindex.com/articles/529881

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