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dc.contributor.authorOnatski, A.
dc.date.accessioned2018-04-06T13:28:42Z
dc.date.available2018-04-06T13:28:42Z
dc.date.issued2018-01-25
dc.identifier.otherCWPE1808
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/274650
dc.description.abstractWe consider large factor models where factors' explanatory power does not strongly dominate the explanatory power of the idiosyncratic terms asymptotically. We find the first and second order asymptotics of the principal components estimator of such a weak factors as the dimensionality of the data and the number of observations tend to infinity proportionally. The principal components estimator is inconsistent but asymptotically normal.
dc.relation.ispartofseriesCambridge Working Papers in Economics
dc.rightsAll Rights Reserveden
dc.rights.urihttps://www.rioxx.net/licenses/all-rights-reserved/en
dc.subjectLarge factor models
dc.subjectprincipal components
dc.subjectphase transition
dc.subjectweak factors
dc.subjectinconsistency
dc.subjectasymptotic distribution
dc.subjectMarčenko-Pastur law.
dc.titleAsymptotics of the principal components estimator of large factor models with weak factors and i.i.d. Gaussian noise.
dc.typeWorking Paper
dc.publisher.institutionUniversity of Cambridge
dc.publisher.departmentFaculty of Economics
dc.identifier.doi10.17863/CAM.21783


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