Abstract: The four-factor dynamic term structure model is built up in this paper to improve substantially to widely used Nelson-Siegel model and tree-factor dynamic Nelson-Siege model. An additional slop factor is added to tree-factor dynamic model to make it more flexible in fitting and forecasting the short end of yield curve. Our model nests the three-factor dynamic Nelson-Siegel model as a special case and these two models can be compared directly by likelihood ratio. The model is formulated in state space form (6) and Kalman filtering is employed to construct likelihood. The empirical study is conducted using data from China interbank bond market and the conclusion shows that our double-slope-factor model can capture dynamics in short end of yield curve more accurately and then has a better fitting and forecasting performance than three-factor dynamic Nelson-Siegel model. The likelihood ratio test justifies the need of the additional slop factor. The model in the paper is an extension to those in the literature of term structure of interest rate and can be used in other empirical studies.

Key words: term structure of interest rate, Nelson-Siegel model, state space model