6533b7d4fe1ef96bd12632ac

RESEARCH PRODUCT

Bootstrap validation of links of a minimum spanning tree

Rosario N. MantegnaRosario N. MantegnaLuca MarottaSalvatore MiccichèFederico Musciotto

subject

FOS: Computer and information sciencesStatistics and ProbabilityMultivariate statisticsCorrelation coefficientCovariance matrixReplicaComplex systemMinimum spanning treeCondensed Matter Physics01 natural sciencesSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Minimum spanning tree Bootstrap Planar maximally filtered graph Information filtering Proximity based networks Random matrix theory010305 fluids & plasmasMethodology (stat.ME)0103 physical sciencesStatistics010306 general physicsRandom matrixStatistics - MethodologyMathematics

description

We describe two different bootstrap methods applied to the detection of a minimum spanning tree obtained from a set of multivariate variables. We show that two different bootstrap procedures provide partly distinct information that can be highly informative about the investigated complex system. Our case study, based on the investigation of daily returns of a portfolio of stocks traded in the US equity markets, shows the degree of robustness and completeness of the information extracted with popular information filtering methods such as the minimum spanning tree and the planar maximally filtered graph. The first method performs a "row bootstrap" whereas the second method performs a "pair bootstrap". We show that the parallel use of the two methods is suggested especially for complex systems presenting both a nested hierarchical organization together with the presence of global feedback channels.

yearjournalcountryeditionlanguage
2018-01-01
10.1016/j.physa.2018.08.020http://arxiv.org/abs/1802.03395