Dynamical clustering of exchange rates

Quantitative Finance

Volumn 12, Issue 10, 2012, Pages 1493-1520

  Fenn, Daniel J ^a   Porter, Mason A ^a   Mucha, Peter J ^b,c   McDonald, Mark ^d   Williams, Stacy ^d   Johnson, Neil F ^a,e   Jones, Nick S ^a,f  

^a UNIVERSITY OF OXFORD   (United Kingdom)

^b University of North Carolina at Chapel Hill   (United States)

^c UNIVERSITY OF NORTH CAROLINA   (United States)

^d HSBC   (United Kingdom)

^e UNIVERSITY OF MIAMI   (United States)

^f IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

Community detection; Foreign exchange market; Networks

Indexed keywords

EID: 84867214658     PISSN: 14697688     EISSN: 14697696     Source Type: Journal    
DOI: 10.1080/14697688.2012.668288     Document Type: Article

References (69)

1. Adamcsek, B, Palla, G, Farkas, IJ, Derényi, I and Vicsek, T. 2006. CFinder: locating cliques and overlapping modules in biological networks. Bioinformatics, 22: 1021-1023.
2. Albert, R and Barabási, AL. 2002. Statistical mechanics of complex networks. Rev. Mod. Phys., 74: 47-97.
3. Amaral, LAN and Ottino, JM. 2004. Complex networks. Eur. Phys. J. B, 38: 147-162.
4. Arenas, A, Fernández, A and Gómez, S. 2008. Analysis of the structure of complex networks at different resolution levels. New J. Phys., 10: 053039 doi:10.1088/1367-2630/10/5/053039
5. Asur, S. Parthasarathy, S. and Ucar, D., An event-based framework for characterizing the evolutionary behavior of interaction graphs. In Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'07), 12-15 August 2007, San José, CA, pp. 913-921, 2007 (ACM: New York)
6. Barrat, A, Barthélemy, M and Vespignani, A. 2008. Dynamical Processes on Complex Networks, Cambridge, UK: Cambridge University Press.
7. Berger-Wolf, TY and Saia, J. A framework for analysis of dynamic social networks. In Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'06), 20-23 August 2006, Philadelphia, PA. pp. 523-528, 2006 (ACM: New York)
8. Bernaschi, M, Grilli, L and Vergni, D. 2002. Statistical analysis of fixed income market. Physica A, 308: 381-390.
9. Berry, DA and Lindgren, BW. 1990. Statistics: Theory and Methods, Pacific Grove, CA: Brooks/Cole.
10. Blondel, VD, Guillaume, J, Lambiotte, R and Lefebvre, E. 2008. Fast unfolding of communities in large networks. J. Stat. Mech., 2008, P10008, doi:10.1088/1742-5468/2008/10/P10008
11. Boccara, N. 2003. Modeling Complex Systems, New York: Springer-Verlag.
12. Bollobas, B. Random Graphs, 2nd ed., 2001 (Cambridge University Press: Cambridge, UK)
13. Bouchaud, JP and Potters, M. 2003. Theory of Financial Risk and Derivative Pricing: From Statistical Physics to Risk Management, Cambridge, UK: Cambridge University Press.
14. Brandes, U, Delling, D, Gaertler, M, Görke, R, Hoefer, M, Nikoloski, Z and Wagner, D. 2008. On modularity clustering. IEEE Trans. Knowl. Data Eng., 20: 172-188.
15. Brunnermeier, MK, Nagel, S and Pedersen, LH. 2008. Carry Trades and Currency Crashes., Edited by: Acemoglu, D, Rogoff, K and Woodford, M. Vol. 23, 14473NBER Working Paper Series. Available online at SSRN: http://ssrn.com/abstract=1297722 (accessed 10 April 2010)
16. Caldarelli, G. 2007. Scale-Free Networks, Oxford, UK: Oxford University Press.
17. Dacorogna, MM, Gençay, R, Müller, U, Olsen, RB and Pictet, OV. 2001. An Introduction to High-Frequency Finance, San Diego, CA: Academic Press.
18. Danon, L, Díaz-Guilera, A, Duch, J and Arenas, A. 2005. Comparing community structure identification. J. Stat. Mech., 2005, P09008, doi:10.1088/1742-5468/2005/09/P09008
19. Duda, RO, Hart, PE and Stork, DG. 2001. Pattern Classification, New York: Wiley.
20. Falkowski, T. Bartelheimer, J. and Spiliopoulou, M., Mining and visualizing the evolution of subgroups in social networks. In Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI'06), 18-22 December 2006, Hong Kong, pp. 52-58, 2006 (IEEE Computer Society: Washington, DC)
21. Farkas, I, Ábel, D, Palla, G and Vicsek, T. 2007. Weighted network modules. New J. Phys., 9: 180-198.
22. Fenn, DJ. 2011. "Network communities and the foreign exchange market". In PhD thesis, UK: University of Oxford. Available at http://people.maths.ox.ac.uk/porterm/research/DJF_thesis_FINAL.pdf (accessed 18 April 2012)
23. Fenn, DJ, Porter, MA, McDonald, M, Williams, S, Johnson, NF and Jones, NS. 2009. Dynamic communities in multichannel data: an application to the foreign exchange market during the 2007-2008 credit crisis. Chaos, 19: 033119 doi:10.1063/1.3184538
24. Fortunato, S. 2010. Community detection in graphs. Phys. Rep., 486: 75-174.
25. Fortunato, S and Barthelemy, M. 2007. Resolution limit in community detection. Proc. Natl. Acad. Sci. USA, 104: 36-41.
26. Freeman, LC. 1977. A set of measures of centrality based on betweenness. Sociometry, 40: 35-41.
27. Galati, G, Jeanneau, S and Widera, R. 2002. "Triennial Central Bank Survey: foreign exchange and derivatives market activity in 2001". In Technical report, Bank for International Settlements.
28. Garas, A, Argyrakis, P and Havlin, S. 2008. The structural role of weak and strong links in a financial market network. Eur. Phys. J. B, 63: 265-271.
29. Girvan, M and Newman, MEJ. 2002. Community structure in social and biological networks. Proc. Natl. Acad. Sci. USA., 99: 7821-7826.
30. Good, BH, de Montjoye, YA and Clauset, A. 2010. The performance of modularity maximization in practical contexts. Phys. Rev. E, 81: 046106 doi:10.1103/PhysRevE.81.046106
31. Good, P. 2005. Permutation, Parametric, and Bootstrap Tests of Hypotheses, New York: Springer-Verlag.
32. Górski, AZ, Drożdż, S and Kwapień, J. 2008. Scale free effects in world currency exchange network. Eur. Phys. J. B, 66: 91-96.
33. Guimerà, R and Amaral, LAN. 2005. Functional cartography of complex metabolic networks. Nature, 433: 895-900.
34. Guimerà, R, Sales-Pardo, M and Amaral, LAN. 2004. Modularity from fluctuations in random graphs and complex networks. Phys. Rev. E, 70: 025101 doi:10.1103/PhysRevE.70.025101
35. Heimo, T, Kumpula, J, Kaski, K and Saramäki, J. 2008. Detecting modules in dense weighted networks with the Potts method. J. Stat. Mech., 2008, P08007, doi: 10.1088/1742-5468/2008/08/P08007
36. Hopcroft, J, Khan, O, Kullis, B and Selman, B. 2004. Tracking evolving communities in large linked networks. Proc. Natl. Acad. Sci. USA, 101: 5249-5253.
37. Karrer, B, Levina, E and Newman, MEJ. 2008. Robustness of community structure in networks. Phys. Rev. E, 77: 046119 doi:10.1103/PhysRevE.77.046119
38. Lancichinetti, A, Fortunato, S and Kertéssz, J. 2009. Detecting the overlapping and hierarchical community structure of complex networks. New J. Phys., 11: 033015 doi:10.1088/1367-2630/11/3/033015
39. Liao, TW. 2005. Clustering of time series data-a survey. Pattern Recognit., 38: 1857-1874.
40. Mantegna, RN. 1999. Hierarchical structure in financial markets. Eur. Phys. J. B, 11: 193-197.
41. Mantegna, RN and Stanley, HE. 2000. An Introduction to Econophysics, Cambridge, UK: Cambridge University Press.
42. Matteo, TD, Aste, T and Mantegna, RN. 2004. An interest rates cluster analysis. Physica A, 339: 181-188.
43. McDonald, M, Suleman, O, Williams, S, Howison, S and Johnson, NF. 2005. Detecting a currency's dominance or dependence using foreign exchange network trees. Phys. Rev. E, 72: 046106 doi:10.1103/PhysRevE.72.046106
44. McDonald, M, Suleman, O, Williams, S, Howison, S and Johnson, NF. 2008. Impact of unexpected events, shocking news, and rumours on foreign exchange market dynamics. Phys. Rev. E, 77: 046110 doi:10.1103/PhysRevE.77.046110
45. Meilǎ, M. 2007. Comparing clusterings-an information based distance. J. Multivariate Anal., 98: 873-895.
46. Mucha, PJ, Richardson, T, Macon, K, Porter, MA and Onnela, J-P. 2010. Community structure in time-dependent, multiscale, and multiplex networks. Science, 328: 876-878.
47. Newman, MEJ. 2003. The structure and function of complex networks. SIAM Rev., 45: 167-256.
48. Newman, MEJ. 2004a. Detecting community structure in networks. Eur. Phys. J. B, 38: 321-330.
49. Newman, MEJ. 2004b. Fast algorithm for detecting community structure in networks. Phys. Rev. E, 69: 066133 doi:10.1103/PhysRevE.69.066133
50. Newman, MEJ. 2006a. Finding community structure in networks using the eigenvectors of matrices. Phys. Rev. E, 74: 036104 doi:10.1103/PhysRevE.74.036104
51. Newman, MEJ. 2006b. Modularity and community structure in networks. Proc. Natl. Acad. Sci. USA, 103: 8577-8582.
52. Newman, MEJ and Girvan, M. 2004. Finding and evaluating community structure in networks. Phys. Rev. E, 69: 026113 doi:10.1103/PhysRevE.69.026113
53. Onnela, J-P, Chakraborti, A, Kaski, K, Kertész, J and Kanto, A. 2003. Dynamics of market correlations: taxonomy and portfolio analysis. Phys. Rev. E, 68: 056110 doi:10.1103/PhysRevE.68.056110
54. Onnela, J-P, Kaski, K and Kertész, J. 2004. Clustering and information in correlation based financial networks. Eur. Phys. J. B, 38: 353-362.
55. Onnela, J-P, Saramäki, J, Hyvönen, J, Szabó, G, Lazer, D, Kaski, K, Kertész, J and Barabási, AL. 2007. Structure and tie strengths in mobile communication networks. Proc. Natl. Acad. Sci. USA, 104: 7332-7336.
56. Palla, G, Barabasi, AL and Vicsek, T. 2007. Quantifying social group evolution. Nature, 446: 664-667.
57. Porter, MA, Mucha, PJ, Newman, MEJ and Warmbrand, CM. 2005. A network analysis of committees in the United States House of Representatives. Proc. Natl. Acad. Sci. USA, 102: 7057-7062.
58. Porter, MA, Onnela, J-P and Mucha, PJ. 2009. Communities in Networks. Not. Am. Math. Soc., 56: 1082-1097. 1164-1166
59. Ranaldo, A and Söderlind, P. 2010. Safe haven currencies. Rev. Finance, 14: 385-407.
60. Reichardt, J and Bornholdt, S. 2006. Statistical mechanics of community detection. Phys. Rev. E, 74: 016110 doi:10.1103/PhysRevE.74.016110
61. Restrepo, JG, Ott, E and Hunt, BR. 2006. Characterizing the dynamical importance of network nodes and links. Phys. Rev. Lett., 97: 094102 doi:10.1103/PhysRevLett.97.094102
62. Schelter, B, Winterhalder, M and Timmer, J. 2006. Handbook of Time Series Analysis, Weinheim, Germany: Wiley-VCH.
63. Shalizi, CR, Camperi, MF and Klinkner, KL. 2007. "Discovering functional communities in dynamical networks". In Statistical Network Analysis: Models, Issues, and New Directions, Edited by: Airoldi, EM, Blei, DM, Feinberg, SE, Goldenberg, A, Xing, EP and Zheng, AX. 140-157. New York: Springer-Verlag.
64. Sieczka, P and Holyst, JA. 2009. Correlations in commodity markets. Physica A, 388: 1621-1630.
65. Toyoda, M and Kitsuregawa, M. Extracting evolution of web communities from a series of web archives. In Proceedings of the 14th ACM Conference on Hypertext and Hypermedia (HYPERTEXT'03), 26-30 August, Nottingham, UK, pp. 28-37, 2003 (ACM: New York)
66. Traag, VA and Bruggeman, J. 2009. Community detection in networks with positive and negative links. Phys. Rev. E, 80: 036115 doi:10.1103/PhysRevE.80.036115
67. Traud, AL, Kelsic, ED, Mucha, PJ and Porter, MA. 2011. Comparing community structure to characteristics in online collegiate social networks. SIAM Rev., 53: 526-543.
68. Valente, TW, Coronges, K, Lakon, C and Costenbader, E. 2008. How correlated are network centrality measures?. Connections, 28: 16-26.
69. Wasserman, S and Faust, K. 1994. Social Network Analysis: Methods and Applications, Cambridge, UK: Cambridge University Press.