Abstract
We propose a new dynamic Nelson--Siegel yield curve model, in which the slope and curvature factor loadings are governed by two time-varying factor-specific decay parameters, and the factor shock variance-covariance (SV) follows a stochastic inverse Wishart process. The importance of incorporating the ensemble of the time-varying factor loadings and SV are demonstrated by comparing the proposed model with simpler specifications in terms of statistical and economic criteria. For the statistical evaluation, we examine the out-of-sample yield curve density forecasting performance. The economic value of the model is measured by the utility gain from the bond portfolio optimization of a Bayesian risk-averse investor. According to our out-of-sample experiment using U.S. monthly yield curve data, the time-varying factor loadings and stochastic variance-covariance accommodate gradual structural changes in the yield curve dynamics around an unconventional monetary policy period, thus improving the predictive accuracy and utility gain.
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