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The dynamic Nelson–Siegel (DNS) model and even the Svensson generalization of the model have trouble in fitting the short maturity yields and fail to grasp the characteristics of the Japanese government bonds yield curve, which is flat at the short end and has multiple inflection points. Therefore, a closely related generalized dynamic Nelson–Siegel (GDNS) model that has two slopes and curvatures is considered and compared empirically to the traditional DNS in terms of in-sample fit as well as out-of-sample forecasts. Furthermore, the GDNS with time-varying volatility component, modeled as standard EGARCH process, is also considered to evaluate its performance in relation to the GDNS. The GDNS model unanimously outperforms the DNS in terms of in-sample fit as well as out-of-sample forecasts. Moreover, the extended model that accounts for time-varying volatility outpace the other models for fitting the yield curve and produce relatively more accurate 6- and 12-month ahead forecasts, while the GDNS model comes with more precise forecasts for very short forecast horizons. [ABSTRACT FROM AUTHOR]

The monetary policy targets the short rates; however, during zero interest rate policy (ZIRP), the short end of the yield curve cannot serve as a policy instrument. Relying on the joint yields-macro latent factors model, this study empirically examines the effect of monetary policy stances on term structure and the possible feedback effect on the real sector using the Japanese experience of ZIRP. The analysis indicates that it is the entire term structure that transmits the policy shocks to the real economy rather than the yield spread only. The monetary policy signals pass through the yield curve level and slope factors to stimulate the economic activity. The curvature factor, besides reflecting the cyclical fluctuations of the economy, acts as a leading indicator for future inflation. In addition, policy influence tends to be low as the short end becomes segmented toward medium/long-term of the yield curve. Furthermore, volatility in bond markets is found to be asymmetrically affected by positive and negative shocks and long end tends to be less sensitive to stochastic shocks than the short maturities. The expectation hypothesis of the term structure does not hold during the ZIRP period. [ABSTRACT FROM PUBLISHER]

ABSTRACT This study empirically examines the role of macroeconomic and stock market variables in the dynamic Nelson-Siegel framework with the purpose of fitting and forecasting the term structure of interest rate on the Japanese government bond market. The Nelson-Siegel type models in state-space framework considerably outperform the benchmark simple time series forecast models such as an AR(1) and a random walk. The yields-macro model incorporating macroeconomic factors leads to a better in-sample fit of the term structure than the yields-only model. The out-of-sample predictability of the former for short-horizon forecasts is superior to the latter for all maturities examined in this study, and for longer horizons the former is still compatible to the latter. Inclusion of macroeconomic factors can dramatically reduce the autocorrelation of forecast errors, which has been a common phenomenon of statistical analysis in previous term structure models. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]