Inference on the maximal rank of time-varying covariance matrices using high-frequency data

Markus Reiß and Lars Winkelmann

No 2021/14, Discussion Papers from Free University Berlin, School of Business & Economics

Abstract: We study the rank of the instantaneous or spot covariance matrix ΣX(t) of a multidimensional continuous semi-martingale X(t). Given highfrequency observations X(i/n), i = 0,...,n, we test the null hypothesis rank (ΣX(t))

Keywords: empirical covariance matrix; rank detection; signal detection rate; matrix concentration; eigenvalue perturbation; principal component analysis; factor model; term structure (search for similar items in EconPapers)
Date: 2021
New Economics Papers: this item is included in nep-ecm, nep-mst and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/246077/1/177616220X.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:zbw:fubsbe:202114

DOI: 10.17169/refubium-32210

Access Statistics for this paper

More papers in Discussion Papers from Free University Berlin, School of Business & Economics Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().