Non-stationarities in financial time series, the long range dependence and the IGARCH effects
Thomas Mikosch and
Catalin Starica
Additional contact information
Thomas Mikosch: Dept. Actuarial Mathematics, University of Copenhagen
Econometrics from University Library of Munich, Germany
Abstract:
In this paper we give the theoretical basis of a possible explanation for two stylized facts observed in long log-return series: the long range dependence (LRD) in volatility and the integrated GARCH (IGARCH). Both these effects can be theoretically explained if one assumes that the data is non-stationary (changing unconditional variance).
Keywords: Sample ACF; Garch process; long range dependence; IGARCH; non- stationarities; time-varying unconditional variance (search for similar items in EconPapers)
JEL-codes: C22 C52 (search for similar items in EconPapers)
Pages: 19 pages
Date: 2004-12-08
New Economics Papers: this item is included in nep-fin
Note: Type of Document - pdf; pages: 19
References: Add references at CitEc
Citations: View citations in EconPapers (146)
Downloads: (external link)
https://econwpa.ub.uni-muenchen.de/econ-wp/em/papers/0412/0412005.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:wpa:wuwpem:0412005
Access Statistics for this paper
More papers in Econometrics from University Library of Munich, Germany
Bibliographic data for series maintained by EconWPA ( this e-mail address is bad, please contact ).