Pozzi, Francesco; Aste, Tomaso; Rotundo, G; Di Matteo, Tiziana
One of the main goals in the field of complex systems is the selection and extraction of relevant and meaningful information about the properties of the underlying system from large datasets. In the last years different methods have been proposed for filtering financial data by extracting a structure of interactions from cross-correlation matrices where only few entries are selected by means of criteria borrowed from network theory. We discuss and compare the stability and robustness of two...[Show more]
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