Random, but not so much: A parameterization for the returns and correlation matrix of financial time series

dc.creatorMartins, Andre C. R.
dc.date2007-01-02
dc.date.accessioned2026-07-07T12:07:55Z
dc.date.available2026-07-07T12:07:55Z
dc.descriptionA parameterization that is a modified version of a previous work is proposed for the returns and correlation matrix of financial time series and its properties are studied. This parameterization allows easy introduction of non-stationarity and it shows several of the characteristics of the true, observed realizations, such as fat tails, volatility clustering, and a spectrum of eigenvalues of the correlation matrix that can be understood as an extension of Random Matrix Theory results. The predicted behavior of this parameterization for the eigenvalues is compared with the eigenvalues of Brazilian assets and it is shown that those predictions fit the data better than Random Matrix Theory.
dc.description4 pages, 3 figures
dc.identifierhttps://arxiv.org/abs/physics/0701025
dc.identifierhttp://arxiv.org/abs/physics/0701025
dc.identifierPhysica A, 383, pp. 527-532 (2007)
dc.identifierdoi:10.1016/j.physa.2007.02.108
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/209142
dc.subjectPhysics and Society
dc.subjectData Analysis, Statistics and Probability
dc.subjectStatistical Finance
dc.titleRandom, but not so much: A parameterization for the returns and correlation matrix of financial time series
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