Authors:
Andrii Bielinskyi
1
;
2
;
Vladimir Soloviev
1
;
3
;
Serhii Hushko
2
;
Arnold Kiv
4
;
5
and
Andriy V. Matviychuk
1
;
3
Affiliations:
1
Kryvyi Rih State Pedagogical University, 54 Gagarin Ave., Kryvyi Rih, 50086, Ukraine
;
2
State University of Economics and Technology, 16 Medychna Str., Kryvyi Rih, 50005, Ukraine
;
3
Kyiv National Economic University named after Vadym Hetman, 54/1 Peremogy Avenue, Kyiv, 03680, Ukraine
;
4
Ben-Gurion University of the Negev, P.O.B. 653, Beer Sheva, 8410501, Israel
;
5
South Ukrainian National Pedagogical University named after K. D. Ushynsky, 26 Staroportofrankivska Str., Odesa, 65020, Ukraine
Keyword(s):
High-Order Network, Crash, Complex networks, Multiplex Networks, Visibility Graph, Indicator-Precursor.
Abstract:
Network analysis has proven to be a powerful method to characterize complexity in socio-economic systems, and to understand their underlying dynamical features. Here, we propose to characterize the temporal evolution of higher-order dependencies within the framework of high-order networks. We test the possibility of financial crashes identification on the example of the Dow Jones Industrial Average (DJIA) index. Regarding topological measures of complexity, we see drastic changes in the complexity of the system during crisis events. Using high-order network analysis and topology, we show that, unlike traditional tools, the presented method is the most perspective, comparing to traditional methods of financial time series analysis.