Article(id=1263533690135654972, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1263533678655881533, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1000-4653.2026.02.009, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1744214400000, receivedDateStr=2025-04-10, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1779179507049, onlineDateStr=2026-05-19, pubDate=1777046400000, pubDateStr=2026-04-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1779179507049, onlineIssueDateStr=2026-05-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1779179507049, creator=13701087609, updateTime=1779179507049, updator=13701087609, issue=Issue{id=1263533678655881533, tenantId=1146029695717560320, journalId=1240618002186551303, year='2026', volume='49', issue='2', pageStart='1', pageEnd='163', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1779179504312, creator=13701087609, updateTime=1779179563167, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1263533925629047616, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1263533678655881533, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1263533925629047617, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1263533678655881533, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=78, endPage=86, ext={EN=ArticleExt(id=1263533691993731666, articleId=1263533690135654972, tenantId=1146029695717560320, journalId=1240618002186551303, language=EN, title=Study on fluctuation rules of CCFI main routes based on empirical mode decomposition, columnId=1240655021705065434, journalTitle=Navigation of China, columnName=Port and Waterway Engineering, runingTitle=null, highlight=null, articleAbstract=

With the continuous development of the shipping market, the China Containerized Freight Index (CCFI) serves as an important indicator for measuring the state of the global container shipping market, and research on its fluctuation characteristics is conducted to help market participants better grasp market dynamics and formulate effective market strategies. To address the issue that CCFI fluctuations are influenced by multiple factors, this paper focused on the composition of the CCFI, selected five major representative routes. First, decomposed the freight index of each route using the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) algorithm optimized by particle swarm adaptation. Second, reconstructed the components into high-frequency and low-frequency parts based on the variance contribution rate. Finally, the BEKK-GARCH model was used to analyze the volatility effects of the original series and the three groups of reconstructed series for the selected routes, and the volatility relationships between different route markets were obtained. The research results show that the impact of major events on CCFI fluctuations is profound, while the impact of short-term market behaviors and sudden events is smaller in magnitude, shorter in duration and higher in frequency; bidirectional spillover effects exist among the trend terms of the freight indices of all routes, and these effects are transmitted to one another.

, correspAuthors=Weili Wang, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Weili Wang, Sitian Yin, Yiwen Wang), CN=ArticleExt(id=1263533696095761009, articleId=1263533690135654972, tenantId=1146029695717560320, journalId=1240618002186551303, language=CN, title=中国出口集装箱主要航线运价指数波动研究, columnId=1240655021902197734, journalTitle=中国航海, columnName=水运工程, runingTitle=null, highlight=null, articleAbstract=

随着航运市场的不断发展，中国出口集装箱运价指数（CCFI）作为衡量全球集装箱航运市场状况的重要指标，对其波动特征的研究有助于航运市场参与者更好地把握市场动态，制定有效的市场策略。针对CCFI波动受到多方面因素影响的问题，本文聚焦CCFI的构成，选取5条具有代表性的主要航线，首先采用粒子群自适应优化的改进完全自适应噪声集合经验模态分解（ICEEMDAN）算法对各航线运价指数进行分解；其次，结合方差贡献率将分量重构为高频和低频部分。最后，利用BEKK GARCH模型对选定航线的原始序列及分解重构后的3组序列做波动效应分析，获得不同航线市场间的波动关系。研究结果表明，重大事件冲击对CCFI波动影响深远，而短期市场行为和突发事件影响程度较小、持续时间短且频率高，所有航线运价指数的趋势项之间均存在双向溢出效应，且这种效应相互传导。

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王维莉（1987—），女，博士，副教授，研究方向为物流工程与管理等。

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王维莉（1987—），女，博士，副教授，研究方向为物流工程与管理等。

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