Influence of the time scale on the construction of financial networks

PLoS ONE

Volumn 5, Issue 9, 2010, Pages 1-9

  Emmert Streib, Frank ^a   Dehmer, Matthias ^b  

^a QUEEN'S UNIVERSITY BELFAST   (United Kingdom)

^b Institute for Bioinformatics and Translational Research   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ARTICLE; CALCULATION; DATA ANALYSIS; FINANCIAL MANAGEMENT; MARKETING; RANDOMIZATION; TIME;

FINANCIAL MANAGEMENT; MARKETING; TIME FACTORS;

EID: 77958559413     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0012884     Document Type: Article

References (43)

1. Bar-Yam Y (1997) Dynamics of Complex Systems Perseus Books.
2. Schuster H (2002) Complex Adaptive Systems Scator Verlag.
3. Stanley HE, Amaral LAN, Buldyrev SV, Gopikrishnan P, Plerou V, et al. (2002) Self-organized complexity in economics and finance. Proceedings of the National Academy of Sciences of the USA 99: 2561-2565.
4. Mantegna R, Stanley H (2000) An Introduction to Econophysics: Correlations and Complexity in Finance Cambridge University Press.
5. McCauley J (2004) Dynamics of Markets, Econophysics and Finance Cambridge University Press.
6. Boginski V, Butenko S, Pardalos P (2005) Statistical analysis of financial networks. Computational Statistics and Data Analysis 48: 431-443.
7. Emmert-Streib F, Dehmer M (2010, in press) Identifying Critical Financial Networks of the DJIA: Towards a Network-based Index. Complexity.
8. Mantegna R (1999) Hierarchical structure in financial markets. European Physical Journal B 11: 193-197.
9. Nagurney A, Siokos S (1997) Financial Networks: Statics and Dynamics Springer.
10. Albert R, Barabasi A (2002) Statistical mechanics of complex networks. Rev of Modern Physics 74: 47.
11. Bornholdt S, Schuster H, eds. Handbook of Graphs and Networks: From the Genome to the Internet Wiley-VCH.
12. Emmert-Streib F, Dehmer M, eds. Analysis of Microarray Data: A Network Based Approach Wiley-VCH.
13. Newman MEJ (2003) The structure and function of complex networks. SIAM Review 45: 167-256.
14. Watts D (1999) Small Worlds: The Dynamics of Networks between Order and Randomness Princeton University Press.
15. Onnela JP, Chakraborti A, Kaski K, Kertész J, Kanto A (2003) Dynamics of market correlations: Taxonomy and portfolio analysis. Phys Rev E 68: 056119.
16. Drozdz S, Grümmer F, Ruf F, Speth J (2000) Dynamics of competition between collectivity and noise in the stock market. Physica A 287: 440-449.
17. Kullmann L, Kertész J, Kaski K (2002) Time dependent cross correlations between different stock returns: A directed network of influence. Phys Rev E 66: 026125.
18. Onnela JP, Kaski K, Kertész J (2004) Clustering and information in correlation based financial networks. Eur Phys J B 38: 353-362.
19. Epps T (1979) Comovements in stock prices in the very short run. Journal of the American Statistical Association 74: 291-298.
20. Ding M, Chen Y, Bressler S Handbook of Time Series Analysis, Wiley, chapter Granger causality: Basic theory and application to neuroscience. pp 437-460.
21. Tsay R (2005) Analysis of Financial Time Series Wiley.
22. Kwapien J, Drozdz S, Speth J (2004) Time scales involved in emergent market coherence. Physica A 337: 231-242.
23. Tóth B, Kertész J (2007) On the origin of the epps effect. Physica A 383: 54-58.
24. Emmert-Streib F (2007) The chronic fatigue syndrome: A comparative pathway analysis. Journal of Computational Biology 14: 961-972.
25. Emmert-Streib F, Dehmer M, eds. Medical Biostatistics for Complex Diseases Wiley-Blackwell.
26. Yahoo finance. http://finance.yahoo.com/.
27. Rencher A (2002) Methods of Multivariate Analysis Wiley.
28. Sheskin DJ (2004) Handbook of Parametric and Nonparametric Statistical Procedures RC Press, Boca Raton, FL, 3rd edition.
29. Bunke H (1983) What is the distance between graphs? Bulletin of the EATCS 20: 35-39.
30. Bunke H (2000) Recent developments in graph matching. In: 15th International Conference on Pattern Recognition. volume 2. pp 117-124.
31. Bunke H (2000) Graph matching: Theoretical foundations, algorithms, and applications. In: Proceedings of Vision Interface 2000. pp 82-88.
32. Bunke H, Neuhaus M (2007) Graph matching. exact and error-tolerant methods and the automatic learning of edit costs. In: Cook D, Holder LB, eds. Mining Graph Data Wiley-Interscience. pp 17-32.
33. Kullback S, Leibler R (1951) On information and sufficiency. Ann Math Stat 22: 79-86.
34. Kullback S (1959) Information theory and statistics Wiley.
35. Sornette D (2003) Why Stock Markets Crash: Critical Events in Complex Financial Systems Princeton University Press.
36. Barabasi AL, Albert R (1999) Emergence of scaling in random networks. Science 206: 509-512.
37. Durret R (2006) Random Graph Dynamics Cambridge University Press.
38. Erdös P, Rényi A (1959) On random graphs. I. Publicationes Mathematicae 6: 290-297.
39. Watts D, Strogatz S (1998) Collective dynamics of 'small-world' networks. Nature 393: 440-442.
40. Simon H (1955) On a class of skew distribution functions. Biometrika 42: 425-440.
41. Yule G (1925) A Mathematical Theory of Evolution, Based on the Conclusions of Dr. J. C. Willis, F.R.S. Phil Trans R Soc Lond B 213: 21-87.
42. von Bertalanffy L (1968) General System Theory: Foundation, Development, Application. New York: George Braziller.
43. R Development Core Team (2008) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0.