Document Type : Original Article
Authors
Department of Physics, Shahid Beheshti University, Tehran, Iran
Abstract
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.
Keywords
- A Barabási. “Network science”. Cambridge university press (2016).
- J A Dunne, et al., Proceedings of the National Academy of Sciences 99, 20 (2002) 12917.
- M Boss, et al. Quantitative finance 4, 6 (2004) 677.
- M E Newman. Nature physics 8, 1 (2012) 25.
- S Fortunato. Physics reports 486, 3-5 (2010) 7.
- P J Mucha., et al., science 328, 5980 (2010) 876.
- M Girvan and M E Newman. Proceedings of the national academy of sciences 99, 12 (2002) 7821.
- A Lancichinetti, S Fortunato, and F Radicchi. Physical Review E 78, 4 (2008) 046110.
- L Danon, et al., Journal of Statistical Mechanics: Theory and Experiment 09 (2005) P09008.
- A Lancichinetti, S Fortunato, and F Radicchi, Physical Review 80, 1 (2009) 016118.
- A Pothen, H D Simon, and K P. Liou, SIAM journal on matrix analysis and applications 11, 3 (1990) 430.
- B W Kernighan and S Lin. The Bell system technical journal 49, 2 (1970) 291.
- D Krackhardt and R N Stern, Social psychology quarterly (1988) 123.
- B Karrer and M E Newman, Physical Review E 83, 1 (2011) 016107.
- Z Li, et al., Physical Review E 77, 3 (2008) 036109.
- M. E. Newman, and M. Girvan. Physical Review E 69, 2 (2004) 026113.
- A Medus, et al, Physica A: Statistical Mechanics and its Applications 358, 2-4 (2005) 593.
- R L Breiger, S A Boorman, and P. Arabie, Journal of mathematical psychology 12 (1975) 328.
- P W Holland, K B Laskey, and S Leinhardt, Social networks 5, 2 (1983) 109.
- F Bernardeau, et al., Physics Reports 367, 1-3 (2002) 1.
- A Vafaei Sadr, and S M S Movahed, Monthly Notices of the Royal Astronomical Society 503, 1(2021) 815.
- R K Pathria, and P D Beale, "Statistical Mechanics”, edition. (2011).
- D Enke, M Grauer, and N Mehdiyev, Procedia Computer Science 6 (2011) 201.
- C Y Chiu, et al., Expert Systems with Applications 36, 3 (2009) 4558.
- K J Kim and H Ahn, Expert systems with applications 34, 2 (2008) 1200.
- A J Lee, et al., "An Effective Clustering Approach to Stock Market Prediction" In PACIS. (2010.)
- M S Prieto and A R Allen, Image and Vision Computing 27, 6 (2009) 673.
- M C Münnix, et al., Scientific reports 2 (2012) 644.
- M. E. Newman, Proceedings of the national academy of sciences 103, 23 (2006) 8577.
- F R Chung and F C Graham, No. 92. American Mathematical Soc. (1997).
- M Fiedler, Czechoslovak mathematical journal 23, 2 (1973) 298.
- S Gómez, P Jensen, and A Arenas, Physical Review E 80, 1 (2009) 016114.
- P Ferreira, A Dionísio, and S M S Movahed, Physica A: Statistical Mechanics and its Applications 486 (2017) 730.
- R A Fisher, Biometrika 10, 4 (1915) 507.
- L Laloux, et al., Physical review letters 83, 7 (1999) 1467.
- V. Plerou, et al., Physical Review Letters 83, 7 (1999) 147.
- J P Bouchaud, and M Potters, Cambridge university press, (2003).
- M Tumminello, F Lillo, and R N Mantegna, AIP Conference Proceedings. American Institute of Physics 965 (2007) 1
- E F Fama., et al. Financial Analysts Journal 49, 1 (1993) 37.
- M Marina, Journal of multivariate analysis 98, 5 (2007) 873.
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