ASYMPTOTICS FOR TIME-VARYING VECTOR MA($\infty $) PROCESSES
提出一类新的时变向量无穷阶移动平均过程，用于建模时变依赖结构并建立多元时间序列模型的渐近理论，通过模拟和真实数据验证了其经验相关性。
This paper introduces a new class of time-varying vector moving average processes of infinite order. These processes serve dual purposes: (1) they can be used to model time-varying dependence structures, and (2) they can be used to establish asymptotic theories for multivariate time series models. To illustrate these two points, we first establish some fundamental asymptotic properties and use them to infer the trending term of a vector moving average infinity process. We then investigate a class of time-varying VARX models. Finally, we demonstrate the empirical relevance of the theoretical results using extensive simulated and real data studies.