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.

In empirically exploring the link between funding liquidity and market liquidity, the greatest challenge is to designate a suitable market that shows such linkages. In this respect, the 15-year Japanese floating (JF)-rate bond market, characterized by the lack of diversity among highly leveraged trading strategies, is an ideal case for investigation. A clean measure of market liquidity, liquidity discount rate (LDR), is estimated from JF prices and the LDR is found to be intertwined with funding liquidity only during the crisis. The deterioration of funding liquidity precedes that of the LDR, thus providing evidence of the outbreak of liquidity spiral.

Review of Finance, 2018, 1213–1247. doi: 10.1093/rof/rfx006 This article has been updated to re-order the authors as above and to add an additional citation in footnote 11.