Correlation filtering in financial time series
We apply a method to filter relevant information from the correlation coefficient matrix by extracting a network of relevant interactions. This method succeeds to generate networks with the same hierarchical structure of the Minimum Spanning Tree but containing a larger amount of links resulting in a richer network topology allowing loops and cliques. In Tumminello et al., 1 we have shown that this method, applied to a financial portfolio of 100 stocks in the USA equity markets, is pretty...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of SPIE Noise and Fluctuations in Econophysics and Finance|
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