Revealing the associations among stocks is fundamental for unveiling the underlying rules of global stock markets. In this work, we propose a combined entropy–complex network framework that detects fluctuation connections among stock prices. The results demonstrate that global stock markets show high uncertainty (high entropy). Based on our analysis of the system's symmetry and dominant correlation fluctuation patterns, we identified the least uncertain stock pair in the market: DEU and FRA. We also revealed the most reliable stocks as references for every stock. Quantifying the uncertainty found in global stock markets and identifying the driving fluctuation patterns can benefit investors by decreasing risk.

中文翻译：

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全球股市波动相关性的不确定性


揭示股票之间的关联性对于揭示全球股票市场的基本规则至关重要。在这项工作中，我们提出了一个组合的熵复杂网络框架，用于检测股票价格之间的波动联系。结果表明，全球股票市场表现出高度不确定性（高熵）。根据我们对系统对称性和主要相关波动模式的分析，我们确定了市场上不确定性最小的股票对：DEU 和 FRA。我们还透露了最可靠的股票作为每只股票的参考。量化全球股票市场的不确定性并确定驱动波动模式可以通过降低风险来使投资者受益。