Examining the Nelson-Siegel Class of Term Structure Models: In-Sample Fit versus Out-of-Sample Forecasting Performance

56 Pages Posted: 12 Jun 2007 Last revised: 20 Oct 2007

See all articles by Michiel De Pooter

Michiel De Pooter

Board of Governors of the Federal Reserve System

Date Written: September 23, 2007

Abstract

In this paper I examine various extensions of the Nelson and Siegel (1987) model with the purpose of fitting and forecasting the term structure of interest rates. As expected, I find that using more flexible models leads to a better in-sample fit of the term structure. However, I show that the out-of-sample predictability improves as well. A four-factor model, which adds a second slope factor to the three-factor Nelson-Siegel model, forecasts particularly well. Especially with a one-step state-space estimation approach the four-factor model produces accurate forecasts and outperforms competitor models across maturities and forecast horizons. Subsample analysis shows that this outperformance is also consistent over time.

Keywords: Term structure of interest rates, Nelson-Siegel, Svensson, Forecasting, State-space model

JEL Classification: E4, C5, C32

Suggested Citation

De Pooter, Michiel, Examining the Nelson-Siegel Class of Term Structure Models: In-Sample Fit versus Out-of-Sample Forecasting Performance (September 23, 2007). Available at SSRN: https://ssrn.com/abstract=992748 or http://dx.doi.org/10.2139/ssrn.992748

Michiel De Pooter (Contact Author)

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States

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