Estimating Chinese Treasury yield curves with Bayesian smoothing splines
Xiaojun Tong, Zhuoqiong Chong He,Dongchu Sun
An improved Bayesian smoothing spline (BSS) model is developed to estimate the term structure of Chinese Treasury yield curves. The developed BSS model has a flexible function form which can model various yield curve shapes. As a nonparametric method different from Jarrow–Ruppert–Yu’s penalized splines, the BSS model does not need to choose the number of and locations for knots. Instead, this BSS model obtains the smoothing parameter as a by-product that does not need to be estimated. Furthermore, a dimension reduction procedure is developed to calculate an inverse matrix when implementing this BSS model. Finally, simulation results and an application illustrate the BSS model outperforms traditional parametric models and the penalized spline model.