摘要
矩阵型截面数据时间序列的优点在于可以同时刻画多个对象的多个属性.本文重点研究了矩阵型截面数据时间序列的自回归模型,给出了该模型的参数估计、模型识别、白噪声检验三个方面的理论结果.最后再利用矩阵型截面数据时间序列自回归模型,对两支银行股的日收益率序列和日成交量变化率序列进行建模分析.
The advantage of time series with matrix cross-section data is that multiple attributes of multiple objects can be characterized simultaneously.This paper focuses on autoregression model of time series with matrix cross-section data and presents the methods of parameter estimation,model identification and white noise test.Finally,the daily yield series and daily volume change rate series of two bank stocks are analyzed by this model.
作者
吴述金
华楠
Shu Jin WU;Nan HUA(Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE,School of Statistics,East China Normal University,Shanghai 200062,P.R.China)
出处
《数学学报(中文版)》
CSCD
北大核心
2022年第6期1093-1104,共12页
Acta Mathematica Sinica:Chinese Series
基金
国家自然科学基金资助项目(11471120)。
关键词
矩阵型截面数据时间序列
参数估计
似然比检验
白噪声检验
time series with matrix cross-section data
parameter estimation
likelihood ratio test
whitenoisetest