Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/195450 
Year of Publication: 
2018
Citation: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 6 [Issue:] 1 [Publisher:] MDPI [Place:] Basel [Year:] 2018 [Pages:] 1-21
Publisher: 
MDPI, Basel
Abstract: 
Several modified estimation methods of the memory parameter have been introduced in the past years. They aim to decrease the upward bias of the memory parameter in cases of low frequency contaminations or an additive noise component, especially in situations with a short-memory process being contaminated. In this paper, we provide an overview and compare the performance of nine semiparametric estimation methods. Among them are two standard methods, four modified approaches to account for low frequency contaminations and three procedures developed for perturbed fractional processes. We conduct an extensive Monte Carlo study for a variety of parameter constellations and several DGPs. Furthermore, an empirical application of the log-absolute return series of the S&P 500 shows that the estimation results combined with a long-memory test indicate a spurious long-memory process.
Subjects: 
spurious long memory
semiparametric estimation
low frequency contamination
perturbation
Monte Carlo simulation
JEL: 
C13
C14
C22
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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