Template-Type: ReDIF-Paper 1.0
Author-Name: Exterkate, P.
Author-Name-Last: Exterkate
Author-Name-First: Peter
Author-Name: van Dijk, D.J.C.
Author-Name-Last: van Dijk
Author-Name-First: Dick
Author-Person: pva27
Author-Name: Heij, C.
Author-Name-Last: Heij
Author-Name-First: Christiaan
Author-Name: Groenen, P.J.F.
Author-Name-Last: Groenen
Author-Name-First: Patrick
Author-Person: pgr229
Title: Forecasting the Yield Curve in a Data-Rich Environment using the Factor-Augmented Nelson-Siegel Model
Abstract: Various ways of extracting macroeconomic information from a data-rich environment are compared with the objective of forecasting yield curves using the Nelson-Siegel model. Five issues in factor extraction are addressed, namely, selection of a subset of the available information, incorporation of the forecast objective in constructing factors, specification of a multivariate forecast objective, data grouping before constructing factors, and selection of the number of factors in a data-driven way. Our empirical results show that each of these features helps to improve forecast accuracy, especially for the shortest and longest maturities. The data-driven methods perform well in relatively volatile periods, when simpler models do not suffice.
Creation-Date: 2010-02-23
File-URL: https://repub.eur.nl/pub/18254/EI2010-06.pdf
File-Format: application/pdf
Series: RePEc:ems:eureir
Number: EI 2010-06
Keywords: Nelson-Siegel model, factor extraction, variable selection, yield curve prediction
Handle: RePEc:ems:eureir:18254