We propose a new time varying correlation coefficient, which is a local correlation measure of a pair of time series. The time varying correlation coefficient is locally estimated using a nonparametric kernel method. Asymptotic normality of the estimated time varying correlation is established, which allows us to construct statistical methods of confidence interval and hypothesis tests. Finite sample validity of the proposed methods are demonstrated by a Monte–Carlo study. The proposed time varying correlation coefficient method is well illustrated by an analysis of five sets of world major stock price index returns.

中文翻译：

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时变相关系数的非参数估计

我们提出了一个新的时变相关系数，它是一对时间序列的局部相关度量。时变相关系数是使用非参数核方法进行局部估计的。建立了估计的时变相关性的渐近正态性，这使我们能够构建置信区间和假设检验的统计方法。蒙特卡洛研究证明了所提出方法的有限样本有效性。通过分析五组世界主要股票价格指数回报，很好地说明了所提出的时变相关系数方法。