Spectrum, intensity and coherence in weighted networks of a financial market

Gergely Tibély, Jukka Pekka Onnela, Jari Saramäki, Kimmo Kaski, János Kertész

Research output: Contribution to journalArticlepeer-review

Abstract (may include machine translation)

We construct a correlation matrix based financial network for a set of New York Stock Exchange (NYSE) traded stocks with stocks corresponding to nodes and the links between them added one after the other, according to the strength of the correlation between the nodes. The eigenvalue spectrum of the correlation matrix reflects the structure of the market, which also shows in the cluster structure of the emergent network. The stronger and more compact a cluster is, the earlier the eigenvalue representing the corresponding business sector occurs in the spectrum. On the other hand, if groups of stocks belonging to a given business sector are considered as a fully connected subgraph of the final network, their intensity and coherence can be monitored as a function of time. This approach indicates to what extent the business sector classifications are visible in market prices, which in turn enables us to gauge the extent of group-behaviour exhibited by stocks belonging to a given business sector.

Original languageEnglish
Pages (from-to)145-150
Number of pages6
JournalPhysica A: Statistical Mechanics and its Applications
Volume370
Issue number1
DOIs
StatePublished - 1 Oct 2006
Externally publishedYes

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