Boudt, Kris, Danielsson, Jon ORCID: 0009-0006-9844-7960 and Laurent, Sebastien (2013) Robust forecasting of dynamic conditional correlation GARCH models. International Journal of Forecasting, 29 (2). pp. 244-257. ISSN 0169-2070
Full text not available from this repository.Abstract
Large one-off events cause large changes in prices, but may not affect the volatility and correlation dynamics as much as smaller events. In such cases, standard volatility models may deliver biased covariance forecasts. We propose a multivariate volatility forecasting model that is accurate in the presence of large one-off events. The model is an extension of the dynamic conditional correlation (DCC) model. In our empirical application to forecasting the covariance matrix of the daily EUR/USD and Yen/USD return series, we find that our method produces more precise out-of-sample covariance forecasts than the DCC model. Furthermore, when used in portfolio allocation, it leads to portfolios with similar return characteristics but lower turnovers, and hence higher profits.
Item Type: | Article |
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Official URL: | http://www.elsevier.com/wps/find/journaldescriptio... |
Additional Information: | © 2012 International Institute of Forecasters |
Divisions: | Finance Financial Markets Group |
Subjects: | H Social Sciences > HG Finance |
Date Deposited: | 05 Mar 2013 12:50 |
Last Modified: | 04 Dec 2024 21:42 |
Funders: | Dutch Science Foundation |
URI: | http://eprints.lse.ac.uk/id/eprint/37389 |
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