Dynamic multifactor clustering of financial networks

Research output: Contribution to journalArticlepeer-review

Abstract

We investigate the tendency for financial instruments to form clusterswhen there are multiple factors influencing the correlation structure. Specifically, we consider a stock portfolio which contains companies from different industrial sectors, located in several different countries. Both sector membership and geography combine to create a complex clustering structure where companies seem to first be divided based on sector, with geographical subclusters emerging within each industrial sector. We argue that standard techniques for detecting overlapping clusters and communities are not able to capture this type of structure and show how robust regression techniques can instead be used to remove the influence of both sector and geography from the correlation matrix separately. Our analysis reveals that prior to the 2008 financial crisis, companies did not tend to form clusters based on geography. This changed immediately following the crisis, with geography becoming a more important determinant of clustering structure.
Original languageEnglish
Article number022809
Number of pages8
JournalPhysical Review E
Volume89
Publication statusPublished - 19 Feb 2014

Fingerprint

Dive into the research topics of 'Dynamic multifactor clustering of financial networks'. Together they form a unique fingerprint.

Cite this