本研究以台灣公債市場為研究對象,並利用Nelson-Siegel模型與Nelson-Siegel-Svensson模型作為研究基礎,比較利率期限結構配適能力之優劣。此外在增進模型平滑度的前題下,利用GCV模型、VRP模型與Anderson-Sleath模型對Nelson-Siegel模型與Nelson-Siegel-Svensson模型加以結合。實證結果發現,Nelson-Siegel模型在結合GCV模型、VRP模型與Anderson-Sleath模型之創新後,在平滑度上皆較原Nelson-Siegel模型更為優良。而Nelson-Siegel-Svensson模型則以結合GCV模型後,能提供較佳之平滑度。當同時考量精確度與平滑度之配適能力後,本文認為在Nelson-Siegel模型中,以結合Anderson-Sleath模型能提供較佳之估計結果;Nelson-Siegel-Svensson模型則以結合GCV之模型,可以提供較佳的估計結果。
The purpose of this paper is to compare the fitting performances of the estimation of the term structure of Taiwan Government Bonds market based on the Nelson-Siegel and the Nelson-Siegel-Svesson model. Three fitting-smoothness improving models (the GCV, VRP and Anderson-Sleath model) are used to increase their fitting performances in accuracy and smoothness. The empirical results indicate that the Nelson-Siegel corrected by the GCV, VRP and Anderson-Sleath model produces better smoothness. The Nelson-Siegel-Svesson corrected by the GCV model also has a better fitting-smoothness result, If we take both the fitting accuracy and smoothness into consideration, the Nelson-Siegel corrected by Anderson-Sleath model and the Nelson-Siegel-Svesson corrected by the GCV model are better choices.