A test of general asymmetric dependence
提出一种修正的互信息度量来捕捉两个随机变量之间的非对称依赖关系，并基于此构建检验方法。模拟显示该检验比现有方法更有效，应用于美国及其他发达国家股票组合与市场收益数据，发现显著的非对称依赖，且市场下行时依赖更强。
Summary We propose a modified mutual information measure to capture general asymmetric dependence between two random variables. Based on this measure, we propose a test of asymmetric dependence and examine its finite‐sample performance. We show that our test has better power than competing tests with alternative dependence measures. Using the new test, we find significant asymmetric dependence in returns of commonly used stock portfolios and the market return both in the US and other developed countries. Further, the dependence between developed country markets and the US market is stronger when both markets are in a downturn.