This article employs an Empirical Mode Decomposition (EMD)-based multiresolution causality approach to explore the scale-by-scale interconnectedness between Bitcoin and the stock markets of Gulf Cooperation Council (GCC) countries. EMD is utilized to decompose signals into intrinsic mode functions (IMFs), which delineate variations across different frequency scales, thus facilitating the identification of distinct oscillations and trends within the signals. The study reveals a significant positive connectedness between Bitcoin and most GCC stock markets, albeit with some variations observed across countries and time periods. Employing multiresolutional causal analysis through EMD provides a valuable framework for examining the nonlinear relationships among financial assets, offering insights into Bitcoin’s potential as a diversification tool in certain periods within GCC stock markets.

中文翻译：

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GCC 股票市场上比特币的多解析因果关系：利用 EMD-Granger 分析方法

本文采用基于经验模态分解（EMD）的多分辨率因果关系方法来探讨比特币与海湾合作委员会（GCC）国家股票市场之间逐尺度的互联性。 EMD 用于将信号分解为本征模态函数 (IMF)，该函数描绘了不同频率范围内的变化，从而有助于识别信号内的不同振荡和趋势。该研究揭示了比特币与大多数海湾合作委员会股票市场之间存在显着的正相关性，尽管在不同国家和时间段之间观察到了一些差异。通过 EMD 采用多分辨率因果分析，为检查金融资产之间的非线性关系提供了一个有价值的框架，并深入了解比特币在海湾合作委员会股票市场特定时期作为多元化工具的潜力。