dorsal/arxiv
View SchemaCorrelation filtering in financial time series
| Authors | T. Aste, T. Di Matteo, M. Tumminello, R. N. Mantegna |
|---|---|
| Categories | |
| ArXiv ID | physics/0508118 |
| URL | https://arxiv.org/abs/physics/0508118 |
| Journal | in {\it Noise and Fluctuations in Econophysics and Finance}, Edited by D. Abbott, J.-P. Bouchaud, X. Gabaix, J. L. McCauley, Proc. of SPIE, Vol. 5848 (SPIE, Bellingham, WA, 2005) 100-109. (Invited Paper) |
Abstract
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. \cite{TumminielloPNAS05}, we have shown that this method, applied to a financial portfolio of 100 stocks in the USA equity markets, is pretty efficient in filtering relevant information about the clustering of the system and its hierarchical structure both on the whole system and within each cluster. In particular, we have found that triangular loops and 4 element cliques have important and significant relations with the market structure and properties. Here we apply this filtering procedure to the analysis of correlation in two different kind of interest rate time series (16 Eurodollars and 34 US interest rates).
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"abstract": "We apply a method to filter relevant information from the correlation\ncoefficient matrix by extracting a network of relevant interactions. This\nmethod succeeds to generate networks with the same hierarchical structure of\nthe Minimum Spanning Tree but containing a larger amount of links resulting in\na richer network topology allowing loops and cliques. In Tumminello et al.\n\\cite{TumminielloPNAS05}, we have shown that this method, applied to a\nfinancial portfolio of 100 stocks in the USA equity markets, is pretty\nefficient in filtering relevant information about the clustering of the system\nand its hierarchical structure both on the whole system and within each\ncluster. In particular, we have found that triangular loops and 4 element\ncliques have important and significant relations with the market structure and\nproperties. Here we apply this filtering procedure to the analysis of\ncorrelation in two different kind of interest rate time series (16 Eurodollars\nand 34 US interest rates).",
"arxiv_id": "physics/0508118",
"authors": [
"T. Aste",
"T. Di Matteo",
"M. Tumminello",
"R. N. Mantegna"
],
"categories": [
"physics.soc-ph"
],
"journal_ref": "in {\\it Noise and Fluctuations in Econophysics and Finance},\n Edited by D. Abbott, J.-P. Bouchaud, X. Gabaix, J. L. McCauley, Proc. of\n SPIE, Vol. 5848 (SPIE, Bellingham, WA, 2005) 100-109. (Invited Paper)",
"title": "Correlation filtering in financial time series",
"url": "https://arxiv.org/abs/physics/0508118"
},
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