Forecasting term structure of the Japanese bond yields in the presence of a liquidity trap

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.