Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/16221

TitleForecasting of yield curves using local state space reconstruction
Author(s)Mena, Filipe C.
Covas, Eurico
Issue date2011
PublisherSpringer
JournalSpringer Proceedings in Mathematics
Abstract(s)We examine models of yield curves through chaotic dynamical systems whose dynamics can be unfolded using non-linear embeddings in higher dimensions. We refine recent techniques used in the state space reconstruction of spatially extended time series in order to forecast the dynamics of yield curves. We use daily LIBOR GBP data (January 2007-June 2008) in order to perform forecasts over a 1-month horizon. Our method outperforms random walk and other benchmark models on the basis of mean square forecast error criteria.
TypeConference paper
URIhttp://hdl.handle.net/1822/16221
ISBN9783642114557
DOI10.1007/978-3-642-11456-4_16
ISSN2190-5614
Publisher versionhttp://www.springer.com/mathematics/dynamical+systems/book/978-3-642-11455-7
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:CMAT - Artigos em atas de conferências e capítulos de livros com arbitragem / Papers in proceedings of conferences and book chapters with peer review

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