The bulk of crude oil is transported globally via large ocean tankers. Freight rates of these tankers show high volatility, which results in significant financial risks to stakeholders. Several factors drive these freight rates. In this study, we specifically investigate their relationships with oil demand as their major determinant. As both these time series demonstrate nonlinear and non-stationary behaviors, we use an advanced decomposition technique - Complete Ensemble Empirical Mode Decomposition (CEEMD) - to analyze their interrelationships. In this approach, we first extract various constituent cycles from both time series. These cycles are then analyzed in a pairwise fashion to detect co-movements in short-, medium-, and long-terms. Investigating the case of the United States Gulf Coast served by three major world routes, we uncovered various economic cycles as well as time-varying relationships. In general, new short shipping-based cycles were found, in addition to the anticipated medium to long cycles. While no short-term relationship was found, weak to increasingly stronger long-term relationships were uncovered, with oil demand leading the freight rates consistently. Differences across routes were also analyzed and interpreted. Our findings have a direct bearing on vessel acquisition/layoff and chartering decisions as well as for overall oil supply planning.

大部分原油通过大型远洋油轮在全球运输。这些油轮的运价波动很大，给利益相关者带来了重大的财务风险。有几个因素推动了这些运费。在这项研究中，我们专门调查了它们与作为主要决定因素的石油需求的关系。由于这两个时间序列都表现出非线性和非平稳行为，我们使用高级分解技术 - 完全集成经验模式分解 (CEEMD) - 来分析它们的相互关系。在这种方法中，我们首先从两个时间序列中提取各种组成周期。然后以成对的方式分析这些周期，以检测短期、中期和长期的共同运动。调查由世界三大航线服务的美国墨西哥湾沿岸的案例，我们发现了各种经济周期以及随时间变化的关系。总的来说，除了预期的中长周期之外，还发现了新的短周期。虽然没有发现短期关系，但发现长期关系从弱到越来越强，石油需求一直领先于运费。还分析和解释了路线之间的差异。我们的研究结果对船舶采购/裁员和租船决策以及整体石油供应计划有直接影响。石油需求一直引领运价。还分析和解释了路线之间的差异。我们的研究结果对船舶采购/裁员和租船决策以及整体石油供应计划有直接影响。石油需求一直引领运价。还分析和解释了路线之间的差异。我们的研究结果对船舶采购/裁员和租船决策以及整体石油供应计划有直接影响。