Journal of Applied Statistics ( IF 1.5 ) Pub Date : 2020-06-23 , DOI: 10.1080/02664763.2020.1783519 Zequn Sun 1 , Thomas J Fisher 2
ABSTRACT
We study the problem of determining if two time series are correlated in the mean and variance. Several test statistics, originally designed for determining the correlation between two mean processes or goodness-of-fit testing, are explored and formally introduced for determining cross-correlation in variance. Simulations demonstrate the theoretical asymptotic distribution can be ineffective in finite samples. Parametric bootstrapping is shown to be an effective tool in such an enterprise. A large simulation study is provided demonstrating the efficacy of the bootstrapping method. Lastly, an empirical example explores a correlation between the Standard & Poor's 500 index and the Euro/US dollar exchange rate while also demonstrating a level of robustness for the proposed method.
中文翻译:
使用参数引导测试两个时间序列之间的相关性
摘要
我们研究确定两个时间序列的均值和方差是否相关的问题。最初设计用于确定两个平均过程或拟合优度测试之间的相关性的几个测试统计量被探索并正式引入以用于确定方差中的互相关。模拟表明理论上的渐近分布在有限样本中可能无效。在这样的企业中,参数引导被证明是一种有效的工具。提供了一项大型模拟研究,证明了自举方法的有效性。最后,一个实证例子探讨了标准普尔 500 指数与欧元/美元汇率之间的相关性,同时也证明了所提出方法的稳健性水平。