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Adaptive forecasting of the EURIBOR swap term structure

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Author Info
Oliver Blaskowitz (Institute of Statistics and Econometrics, Humboldt-Universität zu Berlin, Germany)
Helmut Herwartz (Institute of Statistics and Econometrics, Christian-Albrechts-Universität zu Kiel, Germany)
Abstract

In this paper we adopt a principal components analysis (PCA) to reduce the dimensionality of the term structure and employ autoregressive (AR) models to forecast principal components which, in turn, are used to forecast swap rates. Arguing in favour of structural variation, we propose data-driven, adaptive model selection strategies based on the PCA|AR model. To evaluate ex ante forecasting performance for particular rates, distinct forecast features, such as mean squared errors, directional accuracy and directional forecast value, are considered. It turns out that, relative to benchmark models, the adaptive approach offers additional forecast accuracy in terms of directional accuracy and directional forecast value. Copyright © 2009 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.1121
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Publisher Info
Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 28 (2009)
Issue (Month): 7 ()
Pages: 575-594
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:jof:jforec:v:28:y:2009:i:7:p:575-594

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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This page was last updated on 2009-11-1.

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