An Alternative Approach for Determining the Time-Varying Decay Parameter of the Nelson-Siegel Model

Sang-Heon Lee ()
Additional contact information
Sang-Heon Lee: KB Kookmin Bank

Computational Economics, 2025, vol. 65, issue 5, No 20, 2965-2990

Abstract: Abstract This paper presents an alternative and straightforward two-step estimation method for the Nelson–Siegel yield curve model. The goal is to generate smoothed time series for the time-varying decay parameter and establish stable yield curve factors. To rectify excessive parameter estimates such as jumps or spikes, the decay parameter is adjusted towards its long-run mean using a closed-form expression. Empirical studies conducted with U.S. Treasury data reveal that this method generates stable and easily interpretable outcomes while the confounding effect, which is characterized by large magnitudes with opposite signs among parameters, is effectively mitigated. In out-of-sample forecasting exercises, the proposed model demonstrates comparable or modest performance compared to other competing models, including the random walk model. In particular, the shifting endpoints technique enhances the overall forecasting ability. Finally, the proposed model demonstrates an effective smoothing effect robustly even when applied to other countries.

Keywords: Nelson–Siegel model; Decay parameter; Yield curve; Smoothness; Shifting endpoints (search for similar items in EconPapers)
JEL-codes: C13 C53 G10 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10614-024-10653-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:compec:v:65:y:2025:i:5:d:10.1007_s10614-024-10653-x

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2

DOI: 10.1007/s10614-024-10653-x

Access Statistics for this article

Computational Economics is currently edited by Hans Amman

More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().