Rank-based entropy tests for serial independence

Cees Diks () and Valentyn Panchenko

No 06-14, CeNDEF Working Papers from Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance

Abstract: In nonparametric tests for serial independence the marginal distribution of the data acts as an infinite dimensional nuisance parameter. The decomposition of joint distributions in terms of a copula density and marginal densities shows that in general empirical marginals carry no information on dependence. It follows that the order of ranks is sufficient for inference, which motivates transforming the data to a pre-specified marginal distribution prior to testing. As a test statistic we use an estimator of the marginal redundancy, which has some desirable properties in the case of transforming to uniform marginals. We numerically study the finite sample properties of these tests when the data are transformed to uniform as well as normal marginals. The performance of the tests is compared with that of the BDS test as well as with a parametric rank-based test against ARCH alternatives.

Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://cendef.uva.nl/binaries/content/assets/subsi ... 14.pdf?1417181781427 (application/pdf)

Related works:
Journal Article: Rank-based Entropy Tests for Serial Independence (2008)
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:ams:ndfwpp:06-14

Access Statistics for this paper

More papers in CeNDEF Working Papers from Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance Dept. of Economics and Econometrics, Universiteit van Amsterdam, Roetersstraat 11, NL - 1018 WB Amsterdam, The Netherlands. Contact information at EDIRC.
Bibliographic data for series maintained by Cees C.G. Diks ().