英文标题：
《Detrending moving-average cross-correlation coefficient: Measuring
cross-correlations between non-stationary series》
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作者：
Ladislav Kristoufek
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最新提交年份：
2013
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英文摘要：
In the paper, we introduce a new measure of correlation between possibly non-stationary series. As the measure is based on the detrending moving-average cross-correlation analysis (DMCA), we label it as the DMCA coefficient $\\rho_{DMCA}(\\lambda)$ with a moving average window length $\\lambda$. We analytically show that the coefficient ranges between -1 and 1 as a standard correlation does. In the simulation study, we show that the values of $\\rho_{DMCA}(\\lambda)$ very well correspond to the true correlation between the analyzed series regardless the (non-)stationarity level. Dependence of the newly proposed measure on other parameters -- correlation level, moving average window length and time series length -- is discussed as well.
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中文摘要：
在本文中，我们引入了一种新的度量可能非平稳序列之间的相关性。由于测量基于去趋势移动平均互相关分析（DMCA），我们将其标记为DMCA系数$\\rho_{DMCA}（\\lambda）$，移动平均窗口长度$\\lambda$。我们分析表明，系数范围在-1和1之间，就像标准相关性一样。在模拟研究中，我们表明$\\rho_{DMCA}（\\lambda）$的值非常符合分析序列之间的真实相关性，无论（非）平稳性水平如何。文中还讨论了新提出的测量方法对其他参数的依赖性——相关性水平、移动平均窗口长度和时间序列长度。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Statistical Finance 统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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