EconStor >
Humboldt-Universität zu Berlin >
Sonderforschungsbereich 649: Ökonomisches Risiko, Humboldt-Universität Berlin >
SFB 649 Discussion Papers, HU Berlin >

Please use this identifier to cite or link to this item:
Title:The merit of high-frequency data in portfolio allocation PDF Logo
Authors:Hautsch, Nikolaus
Kyj, Lada M.
Malec, Peter
Issue Date:2011
Series/Report no.:SFB 649 discussion paper 2011-059
Abstract:This paper addresses the open debate about the effectiveness and practical relevance of highfrequency (HF) data in portfolio allocation. Our results demonstrate that when used with proper econometric models, HF data offers gains over daily data and more importantly these gains are maintained over longer horizons than previous studies have shown. We propose a Multi-Scale Spectral Components model for forecasting high-dimensional covariance matrices based on realized measures employing HF data. Extensive performance evaluation confirms that the proposed approach dominates prevailing methods and validates the intuition that HF data used properly can translate into better portfolio allocation decisions.
Subjects:spectral decomposition
mixing frequencies
factor model
blocked realized kernel
covariance prediction
portfolio optimization
Document Type:Working Paper
Appears in Collections:SFB 649 Discussion Papers, HU Berlin

Files in This Item:
File Description SizeFormat
669220272.pdf992.23 kBAdobe PDF
No. of Downloads: Counter Stats
Download bibliographical data as: BibTeX
Share on:

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.