Local polynomial Whittle estimation of perturbed fractional processes
Frank Nielsen and
Morten Nielsen ()
CREATES Research Papers from Department of Economics and Business Economics, Aarhus University
We propose a semiparametric local polynomial Whittle with noise (LPWN) estimator of the memory parameter in long memory time series perturbed by a noise term which may be serially correlated. The estimator approximates the spectrum of the perturbation as well as that of the short-memory component of the signal by two separate polynomials. Furthermore, an empirical investigation of the 30 DJIA stocks shows that this estimator indicates stronger persistence in volatility than the standard local Whittle estimator.
Keywords: Bias reduction; local Whittle; long memory; perturbed fractional process; semiparametric estimation; stochastic volatility (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8) Track citations by RSS feed
Downloads: (external link)
Journal Article: Local polynomial Whittle estimation of perturbed fractional processes (2012)
Working Paper: Local Polynomial Whittle Estimation Of Perturbed Fractional Processes (2009)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:aah:create:2008-29
Access Statistics for this paper
More papers in CREATES Research Papers from Department of Economics and Business Economics, Aarhus University
Bibliographic data for series maintained by ().