Document Type
Journal Article
Publication Title
Journal of Forecasting
Publisher
Wiley
School
School of Business and Law
RAS ID
54862
Funders
The Sumitomo Foundation
Abstract
The Nelson–Siegel (NS) model is widely used in practice to fit the term structure of interest rates largely due to its high efficacy in the in-sample fit and out-of-sample forecasting of bond yields. In this paper, we compare forecasting performances of estimated yields from the Nelson–Siegel-based models and some simpler time series models, using the daily, weekly, and monthly data during a prolong period of liquidity trap in Japan. We find that the out-of-sample expanding window forecasts by NS-based models in general perform less satisfactory than the competitor models. However, the NS-based models can be useful in forecasting yields over longer horizons and can work well with GARCH-type structures in modeling the conditional volatility.
DOI
10.1002/for.2952
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Comments
Tsui, A. K., Wu, J., Zhang, Z., & Zheng, Z. (2023). Forecasting term structure of the Japanese bond yields in the presence of a liquidity trap. Journal of Forecasting, 42(5), 1205-1227.
. https://doi.org/10.1002/for.2952