Cluster formation and evolution in networks of financial market indices

Algorithmic Finance

Volumn 2, Issue 1, 2013, Pages 3-43

  Junior, Leonidas Sandoval ^a  

^a Instituto de Ensino   (Brazil)

Author keywords

Cluster; Evolution; Financial Markets; Networks

Indexed keywords

EID: 84892621703     PISSN: 21585571     EISSN: 21576203     Source Type: Journal    
DOI: 10.3233/AF-13015     Document Type: Article

References (70)

1. Aste, T., Di Matteo, T., 2005. Correlation filtering in financial time series, Noise and Fluctuations in Econophysics and Finance. Proc. SPIE 5848, 100-109.
2. Ausloos, M., Lambiotte, R., 2007. Clusters or networks of economies Amacroeconomy study through gross domestic product. Physica A 382, 16-21.
3. Bonanno, G., Lillo, F., Mantegna, R.N., 2001. Highfrequency cross-correlation in a set of stocks. Quant Financ. 1, 96-104.
4. Bonanno, G., Caldarelli, G., Lillo, F., Miccichè, S., Vandewalle, N., Mantegna, R.N., 2004. Networks of equities in financial markets. Eur. Phys. J. B 38, 363-371.
5. Borg, I., Groenen, P., 2005. Modern Multidimensional Scaling: Theory and Applications, second ed Springer-Verlag.
6. Borghesi, C., Marsili, M., Miccichè, S., 2007. Emergence of time-horizon invariant correlation structure in financial returns by subtraction of the market mode. Phys. Rev. E 76, 026104.
7. Bouchaud, J.-P., Potters, M., 2011. Financial applications of random matrix theory: A short review In: Akemann, G., Baik, J., Di Francesco, P. (Eds.), The Oxford Handbook of Random Matrix Theory Oxford University Press.
8. Brida, J.G., Risso, W.A., 2008. Multidimensional minimal spanning tree: The Dow Jones case Physica A 387, 5205-5210.
9. Chou, Y., 1975. Statistical Analysis. Holt International, ISBN 0030894220, Sect. 17.9.
10. Coelho, R., Gilmore, C.G., Lucey, B., Richmond, P., Hutzler, S., 2007. The evolution of interdependence in world equity markets - evidence from minimum spanning trees. Physica A 376, 455-466.
11. Conlon, T., Ruskin, H.J., Crane, M., 2009. Crosscorrelations dynamics in financial time series Physica A 388, 705-714.
12. Coronnello, C., Tumminello, M., Lillo, F., Micchichè, S., Mantegna, R.N., 2005. Sector identification in a set of stock return time series traded at the London Stock Exchange. Acta Phys. Pol. B 36, 2653-2679.
13. Coronnello, C., Tumminello, M., Lillo, F., Micchichè, S., Mantegna, R.N., 2007. Economic sector identification in a set of stocks traded at the New York Stock Exchange: A comparative analysis. Proc SPIE 6601, 66010T.
14. Dimov, I.I., Kolm, P.N., Maclin, L., Shiber, D.Y.C., 2009. Hidden noise structure and random matrix models of stock correlations. Working Paper 2009- 4, New York University, Courant Institute of Mathematical Sciences.
15. Drozdz, S., Kwapień, J., Speth, J., 2010. Coherent patterns in nuclei and in financial markets. AIP Conf. Proc. 1261, 256-264.
16. Eryigit, M., Eryigit, R., 2009. Network structure of cross-correlations among the world market indices Physica A 388, 3551-3562.
17. Fenn, D.J., Porter, M.A., Mucha, P.J., McDonald, M., Williams, S., Johnson, N.F., et al., 2010. Dynamical Clustering of Exchange Rates. arXiv:0905.4912v2.
18. Flavin, T., Hurley, M., Rousseau, F., 2002. Explaining stock market correlation: A gravity model approach Manchester Sch. 70, 87-106.
19. Fortunato, S., 2010. Community detection in graphs Phys. Rep. 486, 75-174.
20. Gormus, S., Guloglu, B., Gunes, S., 2011. Determinant of stock market return correlation: An extended gravity model approach. Intl. J. Contem. Econ Admin. Sci. 1, 298-312.
21. Gross, T., Sayama, H., 2009. Adaptive Networks: Theory. Models and Applications (Understanding Complex Systems). Springer.
22. Gross, C., 2010. Complex and Adaptive Dynamical Systems: A Primer, second ed. (Springer Complexity) Springer.
23. Hoyst, J.A. 2012. Network Analysis of Correlation Strength between the Most Developed Countries arXiv:1211.3599v1.
24. Laloux, L., Cizeau, P., Bouchaud, J.-P., Potters, M., 1999. Noise dressing of financial correlation matrices. Phys. Rev. Lett. 83, 1467-1470.
25. Laloux, L., Cizeau, P., Potters, M., Bouchaud, J.-P., 2000. Random matrix theory and financial correlations Math. Models Methods Appl. Sci.
26. Kenett, D.Y., Shapira, Y., Madi, A., Bransburg-Zabary, S., Gur-Gershgoren, G., Ben-Jacob, E., 2011. Index cohesive force analysis reveals that the US market became prone to systemic collapses since 2002 PLoS One 6 (4), e19378.
27. Kenett, D.Y., Tumminello, M., Madi, A., Gur- Gershgoren, G., Mantegna, R.N., Ben-Jacob, E., 2010. Dominating clasp of the financial sector revealed by partial correlation analysis of the stock market. PLoS One 5 (12), e15032.
28. Keskin, M., Deviren, B., Kocalkaplan, Y., 2011 Topology of the correlation networks among major currencies using hierarchical structure methods Physica A 390, 719-730.
29. Kulkarni, V., Deo, N., 2007. Correlation and volatility of an Indian stock market: A random matrix approach. Eur. Phys. J. B 60, 101-109.
30. Kwapień, J., Gworek, S., Drozdz, S., Górski, A. (2009). Analysis of a network structure of the foreign currency exchange market. J. Econ. Interact. Coord. 4, 55-72.
31. Kwapień, J., Gworek, S., Drozdz, S., 2006a. Structure and evolution of the foreign exchange networks. Acta Physica Polonica B 40, 175-194.
32. Kwapień, J., Drozdz, S., Oswiecimka, P., 2006b. The bulk of the stock market correlation matrix is not pure noise. Physica A 359, 589-606.
33. Kwapień, J., Drozdz, S., Górski, A.Z., Oswiecimka, P., 2006. Asymmetric matrices in an analysis of financial correlations. Acta Physica Polonica B 37, 3039-3048.
34. Mantegna, R.N., 1999. Hierarchical structure in financial markets. Eur. Phys. J. B 11, 193.
35. Le Martelot, E., Hankin, C. 2012 Fast Multi-Scale Detection of Relevant Communities. arXiv:1204. 1002.
36. Mehta, M.L., 2004. Random Matrices. Academic Press.
37. Micchichè, S., Bonanno, G., Lillo, F., Mantegna, R.N., 2003. Degree stability of a minimum spanning tree of price return and volatility. Physica A 324, 66-73.
38. Miller, J.H., Page, S.E., 2007. Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity). Princeton University Press.
39. Namaki, A., Jafari, G.R., Raei, R., 2010. Comparing TEPIX as an emerging market with efficient market by Random Matrix Theory. Preprint.
40. Newman, M.E.J., 2006. Modularity and community structure in networks. Proc. Natl. Acad. Sci. USA. 103, 8577-8582.
41. Newman, M.E.J., 2010. Networks, and Introduction. Oxford University Press.
42. Oh, G., Eom, C., Wang, F., Jung, W.-S., Stanley, H.E., Kim, S., 2011. Statistical properties of crosscorrelation in the Korean stock market. Eur. Phys. J. B 79, 55-60.
43. Onnela, J.-P., Chakraborti, A., Kaski, K., Kertész, J., 2002. Dynamic asset trees and portfolio analysis. Eur. Phys. J. B 30, 285-288.
44. Onnela, J.-P., Chakraborti, A., Kaski, K., 2003a. Dynamics of market correlations: Taxonomy and portfolio analysis. Phys. Rev. E 68, 1-12.
45. Onnela, J.-P., Chakraborti, A., Kaski, K., Kertész, J., 2003b. Dynamic asset trees and black monday. Physica A 324, 247-252.
46. Onnela, J.-P., Chakraborti, A., Kaski, K., Kertész, J., Kanto, A., 2003c. Asset trees and asset graphs in financial markets. Phys. Scripta T 106, 48-54.
47. Onnela, J.-P., Kaski, K., Kertész, J., 2004. Clustering and information in correlation based financial networks. Eur. Phys. J. B 38, 353-362.
48. Ormerod, P. (2005). The convergence of European business cycles 1980-2004. Acta Physica Polonica B 36, 2747-2756.
49. Pan, R.K., Sinha, S., 2007. Collective behavior of stock price movements in an emerging market. Phys. Rev. E 76, 1-9.
50. Plerou, V., Gopikrishman, P., Rosenow, B., Amaral, L.A.N., Stanley, H.E., 1999. Universal and nonuniversal properties of cross-correlations in financial time series. Phys. Lett. 83, 1471-1474.
51. Plerou, V., Gopikrishman, P., Rosenow, B., Amaral, L.A.N., Stanley, H.E., 2000. A Random Matrix Theory approach to financial cross-correlations. Physica A 287, 374-382.
52. Plerou, V., Gopikrishman, P., Rosenow, B., Amaral, L.A.N., Guhr, T., Stanley, H.E., 2002. Random matrix approach to cross-correlations in financial data. Phys. Rev. E 65, 066126.
53. Potters, M., Bouchaud, J.-P., Laloux, L., 2005. Financial applications of random matrix theory: Old laces and new pieces. Proceedings of the Cracow conference on "Applications of Random Matrix Theory to economy and other complex systems".
54. Qiu, T., Zheng, B., Chen, G., 2010. Adaptive Financial Networks with Static and Dynamic Thresholds. arXiv:1002.3432v1.
55. Rak, R., Kwapień, J., Drozdz, S., Oswiecimka, P., 2008. Cross-correlations in Warsaw Stock Exchange. Acta Physica Polonica A 114, 561-568.
56. Reimann, S., Tupak, A., 2010. Dynamics on/in Financial Markets: Dynamical Decoupling and Stylized Facts. arXiv:1004.1522v1.
57. Rosenow, B., Plerou, V., Gopikrishnan, P., Amaral, L.A.N., Stanley, H.E., 2002. Application of random matrix theory to study cross-correlations of stock prices. Int. J. Theoret. Appl. Financ. 3, 399-403.
58. Sandoval Jr., L. 2012 Pruning a minimum spanning tree. Physica A 391, 2678-2711. doi:10.1016/j.physa.2011.12.052.
59. Sandoval Jr., L. 2012 A Map of the Brazilian Stock Market. Adv. Complex Syst. 15, 1250042-1- 1250042-40.
60. Sandoval Jr., L. 2012 To Lag or Not to Lag?. arXiv:1201.4586.
61. Sandoval Jr., L., Franca, I.D.P. 2012 Correlation of financial markets in times of crisis. Physica A 391, 187-208.
62. Shapira, Y., Kenett, D.Y., Ben-Jacob, E., 2009. The index cohesive effect on stock market correlations. Eur. Phys. J. B 72, 657-669.
63. Sieczka, P., Hoyst, J.A., 2009. Correlations in commodity markets. Physica A 388, 1621-1630.
64. Sinha, S., Pan, R.K., 2007. Uncovering the internal structure of the Indian financial market: Crosscorrelation behavior in the NSE. In: Econophysics of Markets and Business Networks. Springer, pp. 215-226.
65. Song, D.-M., Tumminello, M., Zhou, W.-X., Mantegna, R.N., 2011. Evolution of worldwide stock markets, correlation structure and correlation based graphs. Phys. Rev. E 84, 026108.
66. Tumminello, M., Aste, T., Di Matteo, T., Mantegna, R.N., 2005. A tool for filtering information in complex systems. Proc. Natl. Acad. Sci. USA. 102, 10421-10426.
67. Tumminello, M., Di Matteo, T., Aste, T., Mantegna, R.N., 2007. Correlation based networks of equity returns sampled at different time horizons. Eur. Phys. J. B 55, 209-217.
68. Tumminello, M., Lillo, F., Mantegna, R.N., 2010. Correlation, hierarchies, and networks in financial markets. J. Econ. Behav. Organ. 75, 40-58.
69. Wilcox, D., Gebbie, T., 2007. An analysis of crosscorrelations in an emerging market. Physica A 375, 584-598.
70. Zhanga, Y., Leea, G.H.T., Wonga, J.C., Kokb, J.L., Prustyb, M., Cheong, S.A., 2011. Will the US Economy Recover in 2010? A minimal spanning tree study. Physica A 390, 2020-2050.