报告题目：An automatic MDDM-based test for martingale difference hypothesis

报告时间：2023-12-30 09:30-10:00

报 告 人：王国长 教授  暨南大学

报告地点：理学院东北楼302

Abstract：To check the  error term whether is a marginal difference sequence (MDS) in the multivariate time series model with parametric conditional mean is a very important problem. Since if the error term is aMDS, which indicates that the proposed models is right, if not, which means that there is a lack of fit in the postulated conditional mean specification and can lead to misleading statistical inferences and suboptimal point forecasts, resulting in erroneous conclusions. The test based on  martingale difference divergence matrix (MDDM) is anuseful statistical method to test the MDS in the multivariate time series model, but the MDDM based tests should specify the number of the lag. To solve this problem, we propose a data-driven MDDM test to select the lag automatically. This test has two advantages over existing tests: firstly, the researcher does not need to specify the lag, since the test automatically chooses this number from the data; secondly, under the null hypothesis, the lag is equal to one and which can save a lot of computational costing. Finally, we use numerical studies including simulation and real data analysis to illustrate the usefulness of the proposed test.