The degree sequence of a scale-free random graph process
Random Structures & Algorithms
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Mining and analysing scale-free protein protein interaction network
International Journal of Bioinformatics Research and Applications
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We consider the problem of analyzing influences in financial networks by studying correlations in stock price movements of companies in the S&P 500 index and measures of influence that can be attributed to each company. We demonstrate that under a novel and natural measure of influence involving cross-correlations of stock market returns and market capitalization, the resulting network of financial influences is Scale Free. This is further corroborated by the existence of an intuitive set of highly influential hub nodes in the network. Finally, it is also shown that companies that have been deleted from the S&P 500 index had low values of influence.