CAJ | 학술논문

将惩罚分位数回归SCAD方法引入样条函数并以此来构建国债利率期限结构模型。该方法可以实现自动选取最优分位数，并同步完成模型中的节点选择和参数估计。样本外预测结果显示，与传统的方法相比，新方法可以有效地选择合适的模型，增加参数估计的稳健性，提高预测的精度，增强利率期限结构定价的准确度。
장징벌분위수회귀SCAD방법인입양조함수병이차래구건국채리솔기한결구모형。해방법가이실현자동선취최우분위수，병동보완성모형중적절점선택화삼수고계。양본외예측결과현시，여전통적방법상비，신방법가이유효지선택합괄적모형，증가삼수고계적은건성，제고예측적정도，증강리솔기한결구정개적준학도。
Penalized quantile regression with the SCAD was introduced into the spline function to build the term structure of interest rates of treasure bills .T his method can automatically select the optimal quantile and complete the model's knot selection and parameter estimation at the same time .The out‐of‐sample forecasting results show that ,compared with the traditional methods , the new method can select the appropriate model effectively ,increase the robustness of parameter estimation ,improve forecast accuracy and enhance the pricing precision of the term structure of interest rates .