国债收益率与高频宏观因子--基于非规则混频利率期限结构模型  

Treasury Bond Yields and High-Frequency Macro-Factor:Based on Irregular Mixed-Frequency Nelson-Siegel Model

作　　者：尚玉皇[1] 张皓越 Shang Yuhuang;Zhang Haoyue

机构地区：[1]西南财经大学中国金融研究院

出　　处：《统计研究》2023年第10期109-123,共15页Statistical Research

基　　金：教育部人文社会科学重点研究基地重大项目“数字金融与金融安全问题研究”(22JJD790069);中央高校基本科研经费项目“数字金融场景下金融安全理论及监测预警研究”(JBK2304143);国家社会科学基金重大项目“中国地方政府债务与金融稳定性研究”(20&ZD081)。

摘　　要：及时反映金融市场与宏观经济的动态作用机制是大数据时代制定前瞻性货币政策和投资决策分析的关键。重大突发事件增加了动态经济机制的不确定性,有必要挖掘高频信息加以识别。为此,本文提出一种非规则混频宏观利率期限结构(IR-MF-NS)模型,并基于我国国债收益率和宏观经济信息进行检验。研究发现:与传统模型相比,新模型国债收益率的拟合效果有所改善;国债收益率期限结构与宏观经济存在相互作用机制,实体经济活动与斜率因子呈负相关关系,这与我国逆周期监管目标相一致;高频曲度因子对通货膨胀产生显著正向持续性冲击,验证了曲度因子在高频数据中发挥重要作用的结论;经济机制受信息频率影响,低频数据的“平滑效应”使得低频经济机制表现出平稳效果;高频数据因为信息波动产生“反转效应”使得低频机制和高频机制出现背离;受到重大突发事件的冲击后,国债收益率与宏观基本面的联动性出现系统性减弱,期限结构因子的预测方差作用降低,而宏观基本面对国债收益率预测方差的贡献增大。Timely reflection of the dynamic mechanism of financial market and macro economy is the key to making forward-looking monetary policies and investment decision analysis in the era of big data.Major emergencies have increased the uncertainty of dynamic mechanism analysis,so that it is necessary to mine more high-frequency information for effective identification.Therefore,an Irregular Mixed-Frequency Macro-Factor Nelson-Siegel(IR-MF-NS)Model is proposed and tested based on Chinese Treasury bond yields and macroeconomic information.As the results show,firstly,compared with the traditional model,the new model shows better sample fitting performance.Secondly,we find a bidirectional mechanism between the term structure of treasury bond yields and the macro economy.There is a negative correlation between the real economic activity and the slope factor,which is consistent with the goal of counter-cyclical regulation in China;and the high-frequency curve factor has a significant positive and persistent impact on inflation,which verifies the conclusion that the curve factor plays an important role in high-frequency data.Thirdly,the mechanism is affected by the information frequency.The“smoothing effect”of low-frequency data makes the low-frequency mechanism show the stable effect.The“reversal effect”caused by information fluctuation in high-frequency data makes the low-frequency mechanism and high-frequency mechanism diverge.Finally,the correlation between treasury bond yields and macro fundamentals weakens systematically after the major emergency,and the contribution of term structure factors to forecasting variance is also weakened,while the macro fundamentals play a more important role in predicting the variance of the treasury bond yields.

关 键 词：高频宏观因子 利率期限结构 非规则混频 

分 类 号：C32[社会学] E32[军事—军事理论] E52