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Forecasting the conditional covariance matrix of a portfolio under long-run temporal dependence Author info | Abstract | Publisher info | Download info | Related research | Statistics Antonio Rubia (Department of Financial Economics, University of Alicante, Alicante, Spain)
Trino-Manuel Ñíguez (Westminster Business School, University of Westminster, London, UK and London School of Economics, London, UK)
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Long-range persistence in volatility is widely modelled and forecast in terms of the so-called fractional integrated models. These models are mostly applied in the univariate framework, since the extension to the multivariate context of assets portfolios, while relevant, is not straightforward. We discuss and apply a procedure which is able to forecast the multivariate volatility of a portfolio including assets with long memory. The main advantage of this model is that it is feasible enough to be applied on large-scale portfolios, solving the problem of dealing with extremely complex likelihood functions which typically arises in this context. An application of this procedure to a portfolio of five daily exchange rate series shows that the out-of-sample forecasts for the multivariate volatility are improved under several loss functions when the long-range dependence property of the portfolio assets is explicitly accounted for. Copyright © 2006 John Wiley & Sons, Ltd.
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting .
Volume (Year): 25 (2006)
Issue (Month): 6 ()
Pages: 439-458
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Handle: RePEc:jof:jforec:v:25:y:2006:i:6:p:439-458Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966
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references Cited by : (explanations , Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.)
Herwartz, Helmut & Golosnoy, Vasyl, 2007.
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Christian Conrad, 2007.
"Non-negativity Conditions for the Hyperbolic GARCH Model ,"
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07-162, KOF Swiss Economic Institute, ETH Zurich.
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