Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/195450 
Erscheinungsjahr: 
2018
Quellenangabe: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 6 [Issue:] 1 [Publisher:] MDPI [Place:] Basel [Year:] 2018 [Pages:] 1-21
Verlag: 
MDPI, Basel
Zusammenfassung: 
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.
Schlagwörter: 
spurious long memory
semiparametric estimation
low frequency contamination
perturbation
Monte Carlo simulation
JEL: 
C13
C14
C22
Persistent Identifier der Erstveröffentlichung: 
Creative-Commons-Lizenz: 
cc-by Logo
Dokumentart: 
Article

Datei(en):
Datei
Größe
352.09 kB





Publikationen in EconStor sind urheberrechtlich geschützt.