This paper uses the high-frequency oil price after ensemble empirical mode decomposition, combines crude oil stocks and the US dollar index to construct co-movement threshold networks according to different periods divided by multiple structural breakpoint method. The results show that in the period of sharp fluctuations in oil prices, the inverse relationship between the US dollar index and high-frequency oil prices is more obvious, and the co-movement network of the three is closer to the “small world network”. After oil prices returned to stable fluctuations, coupled with the weakening role of the United States in leading the global economy, the reverse relationship between the US dollar index and high-frequency oil prices has gradually weakened, and the reverse relationship between stocks and high-frequency oil prices has become increasingly prominent. The research not only reveals the main co-movement characteristics of the three, but also provides a new idea for future research on oil price fluctuations and its influencing factors.

本文利用集合经验模态分解后的高频油价，结合原油股和美元指数，根据不同时期划分的多结构断点法构建联动阈值网络。结果表明，在油价大幅波动期间，美元指数与高频油价的反比关系更加明显，三者的联动网络更接近“小世界网络” . 油价回归稳定波动后，加之美国对全球经济的引领作用减弱，美元指数与高频油价的逆向关系逐渐减弱，而库存与高频油价的逆向关系日益凸显。该研究不仅揭示了三者的主要联动特征，而且为今后研究油价波动及其影响因素提供了新思路。