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Sonderforschungsbereich 649: Ökonomisches Risiko, Humboldt-Universität Berlin >
SFB 649 Discussion Papers, HU Berlin >
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http://hdl.handle.net/10419/56752
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| Title: | | The merit of high-frequency data in portfolio allocation  |
| 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 |
| JEL: | | G11 G17 C58 C14 C38 |
| Document Type: | | Working Paper |
| Appears in Collections: | | SFB 649 Discussion Papers, HU Berlin
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