Hierarchical structure of the German stock market

Expert Systems with Applications

Volumn 37, Issue 5, 2010, Pages 3846-3852

  Brida, J Gabriel ^a   Risso, W Adrián ^b  

^a FREE UNIVERSITY OF BOLZANO   (Italy)

^b UNIVERSITY OF SIENA   (Italy)

Author keywords

Cluster analysis; Financial asset returns; Symbolic time series analysis

Indexed keywords

BOOTSTRAP SIMULATION; FINANCIAL ASSET RETURNS; GERMAN COMPANIES; HIERARCHICAL STRUCTURES; HIERARCHICAL TREE; MINIMAL SPANNING TREE; RANDOM BEHAVIOR; STOCK MARKET; STOCK RETURNS; STRUCTURAL BREAK; STRUCTURAL TOPOLOGIES; SYMBOLIC METHODS; SYMBOLIC TIME SERIES ANALYSIS;

CLUSTER ANALYSIS; COMMERCE; FINANCE; TIME SERIES;

TIME SERIES ANALYSIS;

EID: 73249122065     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2009.11.034     Document Type: Article

References (20)

1. Bollt E.M., Stanford T., Lai Y.C., and Zyczkowski Y.C. What symbolic dynamics do we get with a misplaced partition? On the validity of threshold crossings analysis of chaotic time-series. Physica D 154 (2001) 259-286
2. Bonanno G., Calderelli G., Lillo F., Micciché S., Vandewalle N., and Mantegna R.N. Networks of equities in financial markets. The European Physical Journal B 38 (2004) 363-371
3. Bonanno G., Lillo F., and Mantegna R.N. Level of complexity in financial markets. Physica A 299 (2001) 16-27
4. Brida, J. G., & Risso, W. (2007). Dynamics and structure of the 30 largest North American companies. Available at SSRN: .
5. Brida J.G., and Garrido N. Exploring two inflationary regimes in Latin-American economies: A binary time series analysis. International Journal of Modern Physics C 17 1 (2006) 343-356
6. Daw C.S., Finney C.E.A., and Tracy E.R. A review of symbolic analysis of experimental data. Review of Scientific Instruments 74 (2003) 916-930
7. Efron B. Bootstrap methods: Another look at the Jackknife. The Annals of Statistics 71 (1979) 1-26
8. Gower J.C. Some distance properties of latent root and vector methods used in multivariate analysis. Biometrika 53 3-4 (1966) 325-338
9. Halinen A., and Tornroos J. The role of embeddedness in the evolution of business networks. Scandinavian Journal of Management 14 3 (1998) 187-205
10. Hirata Y., Judd K., and Kilaminster D. Estimating a generating partition from observed time series: Symbolic shadowing. Physical Review E 70 (2004) 016215
11. Kaski K., Onnela J.P., and Chakraborti A. Dynamics of market correlations: Taxonomy and portfolio analysis. Physical Review E 68 (2003) 056110
12. Kurths J., Schwarz U., Witt A., Krampe R.h., and Abel M. Measures of complexity in signal analysis. In: Kratz R.A. (Ed). Chaotic, fractal, and nonlinear signal processing (1996), AIP Press, Woodbury, New York 33-54
13. Mantegna R.N. Hierarchical structure in financial markets. The European Physical Journal B 11 (1999) 193-197
14. Mantegna R.N., and Stanley H.E. An introduction to econophysics: Correlations and complexity in finance (2000), Cambridge University Press, UK
15. Mizuno T., Takayasu H., and Takayasu M. Correlation networks among currencies. Physica A 364 (2006) 336-342
16. Molgedey L., and Ebeling W. Local order, entropy and predictability of financial time series. The European Physical Journal B 15 (2000) 733-737
17. Ortega G., and Matesanz D. Cross-country hierarchical structure and currency crises. International Journal of Modern Physics C 17 03 (2005) 333-341
18. Piccardi C. On the control of chaotic systems via symbolic time series analysis. Chaos 14 4 (2004) 1026-1034
19. Ramal R., Toulouse G., and Virasoro M. Ultrametricity for physicist. Review of Modern Physics 58 3 (1986) 765-788
20. Tang X.Z., Tracy E.R., Boozer A.D., deBrauw A., and Brown R. Symbol sequence statistics in noisy chaotic signal reconstruction. Physical Review E 51 5 (1995) 3871-3889