{"title":"ANALYSIS OF LINKAGE FLUCTUATION IN TIME SERIES DATA OF NICKEL FUTURES PRICE INDEX","authors":"Xiaoci Chen, Guanyu Huo, Gaojie Cao","doi":"10.3846/jbem.2023.20191","DOIUrl":null,"url":null,"abstract":"This paper explores the variation pattern of nickel futures prices using the daily closing levels of the nickel futures price index of the London Futures Exchange and the Shanghai Futures Exchange. The data coarse-graining method is employed to transform the continuous time series data of price index changes into symbols {P, N, M}, which are slid through continuous windows to form the modalities of price index linkage fluctuations. By treating the modalities as nodes and the transformations between them as edges, a weighted directed complex network is constructed to represent the linked volatility of the LME and SHFE nickel futures indices time series. The complex network is applied to analyse the network characteristics and obtain the inner pattern of the linked fluctuations. The results show that the complex network of time series linked volatility of the LME and SHFE nickel futures indices exhibits a power-law nature, with closely linked subgroups formed within it. And the mode transitions within these subgroups follow certain patterns. This paper also identifies core positioned modes and important intermediate modes that reflect the dynamics of nickel prices in reality. The method presented in this paper may be extended to related fields and has good applicability.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3846/jbem.2023.20191","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper explores the variation pattern of nickel futures prices using the daily closing levels of the nickel futures price index of the London Futures Exchange and the Shanghai Futures Exchange. The data coarse-graining method is employed to transform the continuous time series data of price index changes into symbols {P, N, M}, which are slid through continuous windows to form the modalities of price index linkage fluctuations. By treating the modalities as nodes and the transformations between them as edges, a weighted directed complex network is constructed to represent the linked volatility of the LME and SHFE nickel futures indices time series. The complex network is applied to analyse the network characteristics and obtain the inner pattern of the linked fluctuations. The results show that the complex network of time series linked volatility of the LME and SHFE nickel futures indices exhibits a power-law nature, with closely linked subgroups formed within it. And the mode transitions within these subgroups follow certain patterns. This paper also identifies core positioned modes and important intermediate modes that reflect the dynamics of nickel prices in reality. The method presented in this paper may be extended to related fields and has good applicability.
本文利用伦敦期货交易所和上海期货交易所镍期货价格指数的日收盘水平,探讨镍期货价格的变化规律。采用数据粗粒化方法,将价格指数变化的连续时间序列数据转化为符号{P, N, M},通过连续窗口滑动,形成价格指数联动波动模态。通过将模态作为节点,将模态之间的转换作为边,构建了一个加权有向复杂网络来表示LME和SHFE镍期货指数时间序列的关联波动率。应用复杂网络分析了网络特性,得到了连锁波动的内部模式。结果表明,LME和SHFE镍期货指数的时间序列关联波动率的复杂网络表现为幂律性质,其中形成了紧密联系的子群。这些子组中的模式转换遵循一定的模式。本文还确定了反映现实镍价动态的核心定位模式和重要中间模式。本文提出的方法可推广到相关领域,具有良好的适用性。