Interest rates hierarchical structure

T. Di Matteo, T. Aste, S.T. Hyde and S. Ramsden

Physica A: Statistical Mechanics and its Applications, 2005, vol. 355, issue 1, 21-33

Abstract: We propose a general method to study the hierarchical organization of financial data by embedding the structure of their correlations in metric graphs in multi-dimensional spaces. An application to two different sets of interest rates is discussed by constructing triangular embeddings on the sphere. Three-dimensional representations of these embeddings with the correct metric geometry are constructed and visualized. The resulting graphs contain the minimum spanning tree as a sub-graph and they preserve its hierarchical structure. This produces a clear cluster differentiation and allows us to compute new local and global topological quantities.

Keywords: Interest rates; Data clustering; Correlations; Econophysics (search for similar items in EconPapers)
Date: 2005
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437105002724
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:355:y:2005:i:1:p:21-33

DOI: 10.1016/j.physa.2005.02.063

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().