标题： 时变多变量因果过程 显示英文标题

标题： Time-Varying Multivariate Causal Processes

摘要： 在本文中，我们考虑了一类广泛的时间变化多变量因果过程，该过程包含了众多经典和新的例子作为特例。 我们首先证明了我们模型的弱依赖平稳近似存在的定理，这是启动理论发展的基础。 随后，我们考虑了QMLE估计方法，并提供了对系数函数的点估计和同时推断。 此外，我们通过模拟和实际数据例子展示了理论结果。 特别是，我们通过一个应用来评估中国和美国股市之间的条件相关性，展示了研究的实证相关性。我们发现这两个股市之间的相互依赖性随时间增加。 显示英文摘要

摘要： In this paper, we consider a wide class of time-varying multivariate causal processes which nests many classic and new examples as special cases. We first prove the existence of a weakly dependent stationary approximation for our model which is the foundation to initiate the theoretical development. Afterwards, we consider the QMLE estimation approach, and provide both point-wise and simultaneous inferences on the coefficient functions. In addition, we demonstrate the theoretical findings through both simulated and real data examples. In particular, we show the empirical relevance of our study using an application to evaluate the conditional correlations between the stock markets of China and U.S. We find that the interdependence between the two stock markets is increasing over time.