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原文連結
論文資訊
- 類型：已發表論文
- 日期：2009
摘要
We study a dataset containing all financial transactions between the accounts of practically all major financial players within Austria over one year. We empirically analyze transaction 網絡s of money (in and out) flows and report the characteristic 網絡 parameters. We observe a significant dependence of 網絡 topology on the time scales of observation, and remarkably low correlation between node degrees and transaction volume. We further use transaction timeseries of the financial 智能體s to compute covariance matrices and their eigenvalue spectra. Eigenvectors corresponding to eigenvalues deviating from the Marcenko-Pastur law are analyzed in detail. The potential for practical use as an automated detection mechanism for abnormal behavior of financial players is discussed. The opinion expressed in
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