The Dynamic Nelson-Siegel Model withTime-Varying Loadings and Volatility

Joint with: Max I.P. Mallee and Michel van der Wel

In this paper we explore time-varying parameter extensions of the dynamic Nelson-Siegel yield curve model for forecasting multiple sets of interest rates with different

maturities. The Nelson-Siegel model is recently reformulated as a dynamic factor model where the latent factors level, slope and curvature are modelled simultaneously by a

vector autoregressive process. We propose to extend this framework in two directions. First, the factor loadings are made time-varying through a simple single step function

and we show that the model fit increases significantly as a result. The step function can be replaced by a spline function to allow for more smoothness and flexibility. Second, we investigate empirically whether the volatility in interest rates across different time periods is constant. For this purpose, we introduce a common volatility component

that is specified as a spline function of time and scaled appropriately for each series. Based on a data-set that is analysed by others, we present empirical evidence where

time-varying loadings and volatilities in the dynamic Nelson-Siegel framework lead to a significantly increase of the model fit. Finally, we provide an illustration where the

model is applied to an unbalanced dataset. It shows that missing data entries can be estimated accurately.

For more information, contact Frank Schorfheide.