Higher-order clustering patterns in simplicial financial systems
Abstract
The interest in induced higher-order relational and multidimensional structures embedded in the financial complex dataset is considered within the applied algebraic topology framework. The aim is to transcend the binary correlations when the interactions of the underlying system are stored in the entries of the cross-correlation matrix. By applying different criteria, we examined aggregations of firms through higher-order clustering of the financial system. The outcome is the extraction of patterns that appear in assemblages of firms due to their multidimensional properties embedded in the cross-correlation matrices. Results are compatible with classifying firms into clusters due to the industry they belong to. Furthermore, the novel and mixed collections of firms are revealed based on the applied mathematical approach. In the broader context, results shed light on the higher-order organization of interactions embedded in the cross-correlation matrix and, as a consequence, extract patt...erns of collective behavior within a complex system.
Source:
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2024, 34, 1Funding / projects:
- Ministry of Science, Technological Development and Innovation of the Republic of Serbia, institutional funding - 200017 (University of Belgrade, Institute of Nuclear Sciences 'Vinča', Belgrade-Vinča) (RS-MESTD-inst-2020-200017)
DOI: 10.1063/5.0185845
ISSN: 1054-1500
PubMed: 38277133
Scopus: 2-s2.0-85183503958
Collections
Institution/Community
VinčaTY - JOUR AU - Maletić, Slobodan AU - Anđelković, Miroslav PY - 2024 UR - https://vinar.vin.bg.ac.rs/handle/123456789/12716 AB - The interest in induced higher-order relational and multidimensional structures embedded in the financial complex dataset is considered within the applied algebraic topology framework. The aim is to transcend the binary correlations when the interactions of the underlying system are stored in the entries of the cross-correlation matrix. By applying different criteria, we examined aggregations of firms through higher-order clustering of the financial system. The outcome is the extraction of patterns that appear in assemblages of firms due to their multidimensional properties embedded in the cross-correlation matrices. Results are compatible with classifying firms into clusters due to the industry they belong to. Furthermore, the novel and mixed collections of firms are revealed based on the applied mathematical approach. In the broader context, results shed light on the higher-order organization of interactions embedded in the cross-correlation matrix and, as a consequence, extract patterns of collective behavior within a complex system. T2 - Chaos: An Interdisciplinary Journal of Nonlinear Science T1 - Higher-order clustering patterns in simplicial financial systems VL - 34 IS - 1 DO - 10.1063/5.0185845 ER -
@article{ author = "Maletić, Slobodan and Anđelković, Miroslav", year = "2024", abstract = "The interest in induced higher-order relational and multidimensional structures embedded in the financial complex dataset is considered within the applied algebraic topology framework. The aim is to transcend the binary correlations when the interactions of the underlying system are stored in the entries of the cross-correlation matrix. By applying different criteria, we examined aggregations of firms through higher-order clustering of the financial system. The outcome is the extraction of patterns that appear in assemblages of firms due to their multidimensional properties embedded in the cross-correlation matrices. Results are compatible with classifying firms into clusters due to the industry they belong to. Furthermore, the novel and mixed collections of firms are revealed based on the applied mathematical approach. In the broader context, results shed light on the higher-order organization of interactions embedded in the cross-correlation matrix and, as a consequence, extract patterns of collective behavior within a complex system.", journal = "Chaos: An Interdisciplinary Journal of Nonlinear Science", title = "Higher-order clustering patterns in simplicial financial systems", volume = "34", number = "1", doi = "10.1063/5.0185845" }
Maletić, S.,& Anđelković, M.. (2024). Higher-order clustering patterns in simplicial financial systems. in Chaos: An Interdisciplinary Journal of Nonlinear Science, 34(1). https://doi.org/10.1063/5.0185845
Maletić S, Anđelković M. Higher-order clustering patterns in simplicial financial systems. in Chaos: An Interdisciplinary Journal of Nonlinear Science. 2024;34(1). doi:10.1063/5.0185845 .
Maletić, Slobodan, Anđelković, Miroslav, "Higher-order clustering patterns in simplicial financial systems" in Chaos: An Interdisciplinary Journal of Nonlinear Science, 34, no. 1 (2024), https://doi.org/10.1063/5.0185845 . .