We propose an Adaptive Dynamic Nelson-Siegel (ADNS) model to adaptively detect parameter changes and forecast the yield curve. The model is simple yet flexible and can be safely applied to both stationary and nonstationary situations with different sources of parameter changes. For the 3- to...

We characterize the discrete-time arbitrage-free Nelson-Siegel term structure model, prove the uniqueness of the solution for model identification, make specification analysis on its canonical form, and detail the MCMC estimation method with a fast and reliable prior extraction step. Using the...

This paper proposes a generalized arbitrage-free macro finance term structure model with both Nelson-Siegel latent yield factors and observable macro factors. Two subclasses are derived: spanned and unspanned models. In the spanned model, the yields are determined by both the Nelson-Siegel yield...

We derive the discrete-time arbitrage-free Nelson-Siegel class of term structure models with an exact solution and proof of uniqueness. We design a fast and reliable estimation procedure based on reduced-dimension optimization with multistep embedded regressions. After an analytical...