Time-varying multivariate causal processes

被引:1
|
作者
Gao, Jiti [1 ]
Peng, Bin [1 ]
Wu, Wei Biao [2 ]
Yan, Yayi [3 ]
机构
[1] Monash Univ, Dept Econometr & Business Stat, Melbourne, Australia
[2] Univ Chicago, Dept Stat, Chicago, IL USA
[3] Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai, Peoples R China
基金
澳大利亚研究理事会; 中国国家自然科学基金;
关键词
Local linear quasi-maximum likelihood; estimation; Multivariate causal process; Uniform confidence band; VOLATILITY SPILLOVERS; SERIES MODELS; INFERENCE; STATIONARY; GARCH; REGRESSION; ESTIMATORS; TESTS;
D O I
10.1016/j.jeconom.2024.105671
中图分类号
F [经济];
学科分类号
02 ;
摘要
In this paper, we consider a wide class of time -varying multivariate causal processes that nests many classical and new examples as special cases. We first show the existence of a weakly dependent stationary approximation to initiate our theoretical investigation. We then consider a quasi -maximum likelihood estimation (QMLE), and provide both point -wise and uniform inferences to coefficient functions of interest. The theoretical findings are further examined through extensive simulations. Finally, we show empirical relevance of our study by evaluating both temporal and contemporaneous connectedness between the stock markets of China and U.S.
引用
收藏
页数:17
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