We propose a new dynamic Nelson–Siegel yield curve model in which two time-varying factor-specific decay parameters govern the slope and curvature factor loadings, and the factor shock variance–covariance (SV) follows a stochastic inverse Wishart process. The proposed model is compared with simpler specifications in terms of statistical and economic criteria to demonstrate the importance of jointly incorporating time-varying factor loadings and SV. We examine the out-of-sample yield curve density forecasting performance for statistical evaluation. The utility gain from the bond portfolio optimization of a Bayesian risk-averse investor measures the model's economic value. Our out-of-sample experiment using United States monthly yield curve data indicates that the time-varying factor loadings and SV accommodate gradual structural changes in the yield curve dynamics around an unconventional monetary policy period, thereby improving the predictive accuracy and utility gain.
Bibliographical noteFunding Information:
We thank Dukpa Kim and the participants of the 2018 Midwest Econometrics group meeting and seminars held at the Bank of Korea and Korea University for their thoughtful and relevant comments on the paper. This work was supported by the National Research Foundation of Korea, funded by the Ministry of Education of the Republic of Korea ( NRF-2020S1A5A2A01043882 ), Ministry of Science and ICT (NRF-2022M3J6A1063595), and the Korea University Research Grant (K2019551).
© 2023 Elsevier B.V.
- Bond portfolio choice
- Certainty equivalent return
- Out-of-sample density forecasting
- Posterior predictive likelihood
ASJC Scopus subject areas
- Economics and Econometrics