Arbeitspapier
The merit of high-frequency data in portfolio allocation
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.
- Sprache
-
Englisch
- Erschienen in
-
Series: SFB 649 Discussion Paper ; No. 2011-059
- Klassifikation
-
Wirtschaft
Portfolio Choice; Investment Decisions
Financial Forecasting and Simulation
Financial Econometrics
Semiparametric and Nonparametric Methods: General
Multiple or Simultaneous Equation Models: Classification Methods; Cluster Analysis; Principal Components; Factor Models
- Thema
-
spectral decomposition
mixing frequencies
factor model
blocked realized kernel
covariance prediction
portfolio optimization
Portfolio-Management
Zeitreihenanalyse
Korrelation
Prognoseverfahren
Theorie
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Hautsch, Nikolaus
Kyj, Lada M.
Malec, Peter
- Ereignis
-
Veröffentlichung
- (wer)
-
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
- (wo)
-
Berlin
- (wann)
-
2011
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Hautsch, Nikolaus
- Kyj, Lada M.
- Malec, Peter
- Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
Entstanden
- 2011
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