摘要
近年来,经验模态分解类算法逐渐被运用到经济分析中,取得了一系列新的研究进展,特别表现为利用分解重构的原理对经济变量进行多尺度分析或预测。但是,该类算法存在一定问题,如模态混淆、端点效应等,因此使用时需考虑算法的适用性问题。鉴于此,本文首先梳理了经验模态分解类算法的发展及其在经济分析中的应用;其次,针对现有文献在使用该类算法时规范性的不足,介绍了最新经验模态分解类算法,梳理及构建了衡量算法适用性的评价指标;最后,本文把算法存在的问题和评价指标相结合,提出了单变量最优经验模态分解类算法选择流程,并利用具体经济数据进行了实例分析。
In recent years,the empirical modal decomposition algorithms have been applied to economic analysis gradually,and a series of new research progress has been obtained.However,there are some problems in this kind of algorithm,such as modal confusion,endpoint effect,etc.Therefore,the applicability of the algorithm should be considered when using it.Secondly,in view of the normative shortcomings of the existing literature in the use of this kind of algorithm,this paper introduces the latest empirical mode decomposition class algorithm,combs and constructs the evaluation index to measure the applicability of the algorithm.And then,combining the existing problems of the algorithm with the evaluation index,this paper puts forward the selection flow of the single variable optimal empirical mode decomposition class algorithm,and makes an example analysis by using the specific economic data.Finally,combining the existing problems of the algorithm with the evaluation index,this paper puts forward the selection flow of the single variable optimal empirical mode decomposition algorithm,and analyzes the example by using the specific economic data.
作者
陈煌杰
CHEN Huangjie(Zhejiang Gongshang University,Hangzhou Zhejiang 310086)
出处
《西部金融》
2020年第1期14-23,共10页
West China Finance
关键词
经验模态分解类算法
最优选择
经济分析
评价性指标
empirical mode decomposition algorithms
optimal selection
economic analysis
evaluation index
