论文标题
时变多元因果过程
Time-Varying Multivariate Causal Processes
论文作者
论文摘要
在本文中，我们考虑了一类时变的多元因果过程，这些过程将许多经典和新的例子嵌套为特殊情况。我们首先证明了我们的模型存在弱依赖的固定近似值，这是启动理论发展的基础。之后，我们考虑QMLE估计方法，并对系数函数提供点和同时推断。此外，我们通过模拟和真实数据示例证明了理论发现。特别是，我们使用应用程序来评估中国和美国股票市场之间的条件相关性的实证相关性，我们发现两个股票市场之间的相互依存关系随着时间的推移而增加。
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.
