0000000000668913

AUTHOR

Tomaso Aste

showing 3 related works from this author

A tool for filtering information in complex systems

2005

We introduce a technique to filter out complex data-sets by extracting a subgraph of representative links. Such a filtering can be tuned up to any desired level by controlling the genus of the resulting graph. We show that this technique is especially suitable for correlation based graphs giving filtered graphs which preserve the hierarchical organization of the minimum spanning tree but containing a larger amount of information in their internal structure. In particular in the case of planar filtered graphs (genus equal to 0) triangular loops and 4 element cliques are formed. The application of this filtering procedure to 100 stocks in the USA equity markets shows that such loops and cliqu…

Physics - Physics and SocietyComputer scienceComplex systemFOS: Physical sciencesPhysics and Society (physics.soc-ph)Minimum spanning treecomputer.software_genrePlanarHierarchical organizationINTERNETCondensed Matter - Statistical MechanicsComplex data typeMultidisciplinarySmall-world networkStatistical Mechanics (cond-mat.stat-mech)SMALL-WORLD NETWORKSFilter (signal processing)Disordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksComplex networkWEBDYNAMIC ASSET TREESPhysical SciencesGRAPHData miningAlgorithmcomputerMathematicsofComputing_DISCRETEMATHEMATICS
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Correlation based networks of equity returns sampled at different time horizons

2006

We investigate the planar maximally filtered graphs of the portfolio of the 300 most capitalized stocks traded at the New York Stock Exchange during the time period 2001-2003. Topological properties such as the average length of shortest paths, the betweenness and the degree are computed on different planar maximally filtered graphs generated by sampling the returns at different time horizons ranging from 5 min up to one trading day. This analysis confirms that the selected stocks compose a hierarchical system progressively structuring as the sampling time horizon increases. Finally, a cluster formation, associated to economic sectors, is quantitatively investigated.

Physics - Physics and Societynetworks of equity different time horizonsStatistical Finance (q-fin.ST)Equity (finance)Quantitative Finance - Statistical FinanceFOS: Physical sciencesRangingPhysics and Society (physics.soc-ph)Condensed Matter PhysicsElectronic Optical and Magnetic MaterialsCorrelationFOS: Economics and businessBetweenness centralityStock exchangePhysics - Data Analysis Statistics and ProbabilityStatisticsHierarchical control systemPortfolioSampling timeData Analysis Statistics and Probability (physics.data-an)Mathematics
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An interest rates cluster analysis

2004

An empirical analysis of interest rates in money and capital markets is performed. We investigate a set of 34 different weekly interest rate time series during a time period of 16 years between 1982 and 1997. Our study is focused on the collective behavior of the stochastic fluctuations of these time-series which is investigated by using a clustering linkage procedure. Without any a priori assumption, we individuate a meaningful separation in 6 main clusters organized in a hierarchical structure.

Statistics and ProbabilityCollective behaviormedia_common.quotation_subjectFOS: Physical sciencesLinkage (mechanical)computer.software_genrelaw.inventionFOS: Economics and businesslawEconometricsCluster (physics)Cluster analysisCondensed Matter - Statistical Mechanicsmedia_commonStatistical Finance (q-fin.ST)Statistical Mechanics (cond-mat.stat-mech)EconophysicsSeries (mathematics)Quantitative Finance - Statistical FinanceCondensed Matter PhysicsInterest rateCondensed Matter - Other Condensed MatterData miningCapital marketcomputerOther Condensed Matter (cond-mat.other)
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