Modularity cluster finding in financial time series
| العنوان: | Modularity cluster finding in financial time series |
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| المؤلفون: | S. M. S. Movahed, D Papi |
| المصدر: | Iranian Journal of Physics Research, Vol 21, Iss 2, Pp 317-334 (2021) |
| بيانات النشر: | Academic World Research, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Modularity (networks), Theoretical computer science, modularity maximization, Series (mathematics), Computer science, Physics, QC1-999, General Physics and Astronomy, Scale (descriptive set theory), clustering, random matrix theory, Complex network, Matrix (mathematics), econophysics, complex network, Adjacency matrix, Cluster analysis, Random matrix |
| الوصف: | In this paper, relying on the clustering of complex networks that can determine large scale features of the network, we study 48 financial markets across the world. To this end, we develop a modularity maximization method for directed and weighted networks. According to the linear correlation measure, we construct the adjacency matrix, and by using the theory of random matrices, we divide the space of eigenvalues of our matrix into two irrelevant and relevant fragments. By considering the temporal window and its evolution over time series, our results demonstrate that in the vicinity of so-called financial crisis clusters, which are often affected by geographical characteristics, are formed and from the perspective of complex networks, they show more random behavior. |
| تدمد: | 2345-3664 1682-6957 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3786e595a2ada0d61f4ad9cc863a0860 https://doi.org/10.47176/ijpr.21.2.51066 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....3786e595a2ada0d61f4ad9cc863a0860 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 23453664 16826957 |
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