Econometrics as Sorcery
classification
💱 q-fin.ST
nlin.CD
keywords
otherprocessessimilaritiesadoptedapproachassociatedbestclustering
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The paper deals with the problem of identifying the internal dependencies and similarities among a large number of random processes. Linear models are considered to describe the relations among the time series and the energy associated to the corresponding modeling error is the criterion adopted to quantify their similarities. Such an approach is interpreted in terms of graph theory suggesting a natural way to group processes together when one provides the best model to explain the other. Moreover, the clustering technique introduced in this paper will turn out to be the dynamical generalization of other multivariate procedures described in literature.
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