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Modeling and forecasting the yield curve by an extended Nelson-Siegel class of models: A quantile autoregression approach
Department of Finance, Stockholm School of Economics, Stockholm, Sweden.
Department of Economics, Universidade Federal de Minas Gerais - CEDEPLAR, Belo Horizonte, Brazil.
2013 (English)In: Journal of Forecasting, ISSN 0277-6693, E-ISSN 1099-131X, Vol. 32, no 2, p. 111-123Article in journal (Refereed) Published
Abstract [en]

This paper compares the in-sample fitting and the out-of-sample forecasting performances of four distinct Nelson-Siegel class models: Nelson-Siegel, Bliss, Svensson, and a five-factor model we propose in order to enhance the fitting flexibility. The introduction of the fifth factor resulted in superior adjustment to the data. For the forecasting exercise the paper contrasts the performances of the term structure models in association with the following econometric methods: quantile autoregression evaluated at the median, VAR, AR, and a random walk. As a pattern, the quantile procedure delivered the best results for longer forecasting horizons. 

Place, publisher, year, edition, pages
John Wiley & Sons, 2013. Vol. 32, no 2, p. 111-123
Keywords [en]
in-sample fitting, Nelson-Siegel, out-of-sample forecasts, quantile autoregression, yield curve, Autoregression, Out-of-sample forecast, Forecasting, Regression analysis, Curve fitting
National Category
Economics
Identifiers
URN: urn:nbn:se:hj:diva-51455DOI: 10.1002/for.1256ISI: 000314166200002Scopus ID: 2-s2.0-84873085112OAI: oai:DiVA.org:hj-51455DiVA, id: diva2:1516672
Available from: 2021-01-12 Created: 2021-01-12 Last updated: 2021-01-12Bibliographically approved

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De Rezende, Rafael B.

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