反向有约束混频数据模型的市场化利率预测  

Predicting market interest rates via reverse restricted MIDAS model

作　　者：许启发[1,2] 卓杏轩 蒋翠侠[1] XU Qi-fa;ZHUO Xing-xuan;JIANG Cui-xia(School of Management,Hefei University of Technology,Hefei 230009,China;Key Laboratory of Process Optimization and Intelligent Decision-making,Ministry of Education,Hefei 230009,China)

机构地区：[1]合肥工业大学管理学院,合肥230009 [2]过程优化与智能决策教育部重点实验室,合肥230009

出　　处：《管理科学学报》2019年第10期55-71,共17页Journal of Management Sciences in China

基　　金：全国统计科学研究重大资助项目(2019LD05);国家自然科学基金资助项目(71671056)

摘　　要：为准确预测市场化利率,在混频数据抽样(MIDAS)模型和反向无约束混频数据抽样(RU-MIDAS)模型的基础上,提出了反向有约束混频数据抽样模型(RR-MIDAS),使之能够适应各变量之间频率倍差较大时,低频变量对高频变量的分析与预测.选取SHIBOR作为市场化利率的代表,分析其影响因素并开展预测研究.实证结果表明:RR-MIDAS模型能够细致揭示各变量间的实时动态变化关系,表现出很好的拟合效果与预测能力;宏观经济变量和资本市场信息能够在1周甚至1天内对货币供求关系产生影响,进而迅速反映在SHIBOR走势变化上.此外,稳健性检验结果验证了RR-MIDAS模型的实用性以及实证结论的可靠性.In order to accurately predict market interest rates,a novel Reverse Restricted MIDAS(RR-MIDAS)model is developed on the basis of the MIDAS and RU-MIDAS models.The RR-MIDAS model can be applied to the prediction of high frequency variables using low frequency variables when the frequency mis?match is pretty large.SHIBOR is used as a representative of market interest rates,and an empirical analysis of SHIBOR forecasts is conducted.The empirical results show that the RR-MIDAS model outperforms the others in terms of goodness of fit and prediction ability since it is able to explore the dynamic relationships among variables.The results show that both macroeconomic variables and the capital market information could influence the money supply and demand in one week,or even one day,and will quickly lead to a change of SHIBOR.Moreover,robustness tests are implemented to illustrate the efficacy of the RR-MIDAS model and the reliability of the empirical conclusions.

关 键 词：市场化利率 混频数据分析 MIDAS RU-MIDAS RR-MIDAS 

分 类 号：F832[经济管理—金融学]