Gaussian Analysis of Non-Gaussian Time Series

Dimitris Kugiuntzis and Efthimia Bora-Senta

Brussels Economic Review, 2010, vol. 53, issue 2, 295-322

Abstract: A framework is proposed for the analysis of non-Gaussian time series under the Gaussian assumption. The analysis is based on the Gaussian autocorrelation computed from the transform of the sample autocorrelation. It is shown that this approach improves the linear autoregressive fit. We also use it to generate time series that preserve the original autocorrelation and marginal distribution and develop a combined test that discriminates whether a linear stochastic time series is a monotonic or non-monotonic transform of a Gaussian time series. The usefulness of the proposed analysis is demonstrated on stock exchange volumes of several world markets.

Keywords: Non-Gaussian time series; Autocorrelation; Autoregressive models; Surrogate data; Hypothesis testing; International financial markets (search for similar items in EconPapers)
JEL-codes: C12 C22 C51 G15 (search for similar items in EconPapers)
Date: 2010
Note: Numéro Spécial « Special Issue on Nonlinear Financial Analysis :Editorial Introduction » Guest Editor :Catherine Kyrtsou
References: Add references at CitEc
Citations:

Downloads: (external link)
https://dipot.ulb.ac.be/dspace/bitstream/2013/8094 ... IS-BORA-SENTApdf.pdf ARTICLE KUGIUNTZIS-BORA-SENTA 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:bxr:bxrceb:2013/80945

Ordering information: This journal article can be ordered from
http://hdl.handle.ne ... ulb.ac.be:2013/80945

Access Statistics for this article

More articles in Brussels Economic Review from ULB -- Universite Libre de Bruxelles Contact information at EDIRC.
Bibliographic data for series maintained by Benoit Pauwels ().