Uncovering dynamic stock return correlations with multilayer network analysis

Uncovering dynamic stock return correlations with multilayer network analysis

Abstract We apply recent innovations in network science to analyze how correlations of stock returns evolve over time. To illustrate these techniques we study the returns of 30 industry stock portfolios from 1927 to 2014. We calculate Pearson correlation matrices for each year, and apply multilayer...

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Bibliographic Details
Main Authors: Danielle N. Rubin, Danielle S. Bassett, Robert Ready
Format: Article
Language:English
Published: SpringerOpen 2019-06-01
Series:Applied Network Science
Subjects:
Stocks
Industries
Networks
Clustering
Modularity
Community structure
Online Access:http://link.springer.com/article/10.1007/s41109-019-0132-5

Internet

http://link.springer.com/article/10.1007/s41109-019-0132-5

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