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Universität Konstanz >
Center of Finance and Econometrics (CoFE), Universität Konstanz >
CoFE-Diskussionspapiere, Universität Konstanz >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/10419/32171
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Full metadata record
| DC Field | | Value | | Language |
| dc.contributor.author | | Feng, Yuanhua | | en_US |
| dc.contributor.author | | Beran, Jan | | en_US |
| dc.date.accessioned | | 2009-09-17 | | en_US |
| dc.date.accessioned | | 2010-05-14T12:00:38Z | | - |
| dc.date.available | | 2010-05-14T12:00:38Z | | - |
| dc.date.issued | | 2008 | | en_US |
| dc.identifier.uri | | http://hdl.handle.net/10419/32171 | | - |
| dc.description.abstract | | Filtered log-periodogram regression estimation of the fractional differencing parameter d is considered. Asymptotic properties are derived and the effect of filtering on d is investigated. It is shown that the estimator by Geweke and Porter-Hudak (1983) can be improved significantly using a simple family of filters. The essential improvement is based on a binary decision that is asymptotically correct with probability one. The idea is closely related to the well known technique of pre-whitening. | | en_US |
| dc.language.iso | | eng | | en_US |
| dc.publisher | | CoFE Konstanz | | en_US |
| dc.relation.ispartofseries | | Discussion paper series // Zentrum für Finanzen und Ökonometrie, Universität Konstanz 2008,10 | | en_US |
| dc.subject.ddc | | 330 | | en_US |
| dc.subject.keyword | | Filtering | | en_US |
| dc.subject.keyword | | log-periodogram regression | | en_US |
| dc.subject.keyword | | local pre-whitening | | en_US |
| dc.subject.keyword | | fractional differencing parameter | | en_US |
| dc.subject.keyword | | long memory | | en_US |
| dc.title | | Filtered Log-periodogram Regression of long memory processes | | en_US |
| dc.type | | Working Paper | | en_US |
| dc.identifier.ppn | | 608957321 | | en_US |
| dc.rights | | http://www.econstor.eu/dspace/Nutzungsbedingungen | | - |
| Appears in Collections: | | CoFE-Diskussionspapiere, Universität Konstanz
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