A0973
Title: Robust estimation and test for Pearson's correlation coefficient
Authors: Pengfei Liu - Jiangsu Normal University (China) [presenting]
Abstract: Using the idea of grouping under a moderate data framework, the median-of-means type non-parametric estimator is proposed for Pearson's correlation coefficient which has been used widely in various disciplines. Under certain conditions on the growing rate of the number of subgroups, the consistency and asymptotic normality of the proposed estimator are investigated. Furthermore, we construct a new method to test Pearson's correlation coefficient based on the empirical likelihood method for the median. Extensively numerical simulations are designed to demonstrate the superiorities of our estimator. It is shown that the new proposed estimator is quite robust with respect to outliers. Finally, we use the proposed method to study the Pearson's correlation between the open price and the rate of price spread for the Shanghai Stock Exchange composite index from May 18, 2015, to June 21, 2019.
