Uncovering dynamic stock return correlations with multilayer network analysis
@article{Rubin2019UncoveringDS, title={Uncovering dynamic stock return correlations with multilayer network analysis}, author={D. Rubin and D. Bassett and Robert C. Ready}, journal={Applied Network Science}, year={2019}, volume={4}, pages={1-13} }
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 network tools to these correlation matrices to uncover mesoscale architecture in the form of communities. These communities are easily interpretable as groups of industries with highly correlated stock… CONTINUE READING
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