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https://hdl.handle.net/10419/39326
Kompletter Metadatensatz
DublinCore-Feld | Wert | Sprache |
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dc.contributor.author | Hautsch, Nikolaus | en |
dc.contributor.author | Kyj, Lada M. | en |
dc.contributor.author | Oomen, Roel C.A. | en |
dc.date.accessioned | 2009-11-05 | - |
dc.date.accessioned | 2010-08-26T11:57:25Z | - |
dc.date.available | 2010-08-26T11:57:25Z | - |
dc.date.issued | 2009 | - |
dc.identifier.uri | http://hdl.handle.net/10419/39326 | - |
dc.description.abstract | We introduce a regularization and blocking estimator for well-conditioned high-dimensional daily covariances using high-frequency data. Using the Barndorff-Nielsen, Hansen, Lunde, and Shephard (2008a) kernel estimator, we estimate the covariance matrix block-wise and regularize it. A data-driven grouping of assets of similar trading frequency ensures the reduction of data loss due to refresh time sampling. In an extensive simulation study mimicking the empirical features of the S&P 1500 universe we show that the 'RnB' estimator yields efficiency gains and outperforms competing kernel estimators for varying liquidity settings, noise-to-signal ratios, and dimensions. An empirical application of forecasting daily covariances of the S&P 500 index confirms the simulation results. | en |
dc.language.iso | eng | en |
dc.publisher | |aHumboldt University of Berlin, Collaborative Research Center 649 - Economic Risk |cBerlin | en |
dc.relation.ispartofseries | |aSFB 649 Discussion Paper |x2009,049 | en |
dc.subject.jel | C14 | en |
dc.subject.jel | C22 | en |
dc.subject.ddc | 330 | en |
dc.subject.keyword | covariance estimation | en |
dc.subject.keyword | blocking | en |
dc.subject.keyword | realized kernel | en |
dc.subject.keyword | regularization | en |
dc.subject.keyword | microstructure | en |
dc.subject.keyword | asynchronous trading | en |
dc.subject.stw | Varianzanalyse | en |
dc.subject.stw | Schätztheorie | en |
dc.subject.stw | Core | en |
dc.subject.stw | Multivariate Analyse | en |
dc.subject.stw | Theorie | en |
dc.subject.stw | Schätzung | en |
dc.subject.stw | Börsenkurs | en |
dc.subject.stw | Wertpapierhandel | en |
dc.subject.stw | Aktienmarkt | en |
dc.subject.stw | Mikrostrukturanalyse | en |
dc.subject.stw | USA | en |
dc.title | A blocking and regularization approach to high dimensional realized covariance estimation | - |
dc.type | |aWorking Paper | en |
dc.identifier.ppn | 612287025 | en |
dc.rights | http://www.econstor.eu/dspace/Nutzungsbedingungen | en |
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