首页 | 本学科首页   官方微博 | 高级检索  
     检索      

中国钢材交易市场价格发现动态演化研究
引用本文:方雯,冯耕中,陆凤彬,汪寿阳.中国钢材交易市场价格发现动态演化研究[J].系统工程理论与实践,2019,39(1):49-59.
作者姓名:方雯  冯耕中  陆凤彬  汪寿阳
作者单位:1. 西安电子科技大学 经济与管理学院, 西安 710126;2. 西安交通大学 管理学院, 西安 710049;3. 西安交通大学过程控制与效率工程教育部重点实验室, 西安 710049;4. 中国科学院 数学与系统科学研究院, 北京 100190
基金项目:教育部人文社科基金青年项目(15YJC790017);国家自然科学基金青年项目(71602153);陕西省软科学研究计划一般项目(2017KRM117)
摘    要:中国钢材交易市场拥有三种类型:现货、期货和电子交易市场.它们的价格信号对基本面信息的反映能力如何,市场价格发现功能呈现何种动态演化趋势,是产业链成员与政策制定者关注热点.依据向量误差修正原理和条件异方差模型,分析过去的市场信息对多个市场动态条件协方差阵的影响,建立时变信息份额模型,研究中国钢材市场长区间价格发现功能的动态演化.研究显示:热卷板期货上市前,电子交易市场价格发现功能优于现货市场;期货上市后,电子交易市场、期货市场和现货市场都对价格发现过程有所贡献.现货市场价格发现功能呈现较好动态演化趋势,多数时期对价格发现过程的贡献大于其它两类市场.尽管电子交易市场在价格发现过程中的角色由主导者演化为从属者,但其功能发挥较稳定,亦不时具有最先反映基本面信息的能力.在中国钢材市场,保证金水平高低、交易量多寡,以及流动性强弱,都未显示出与价格发现功能有方向性关联.

关 键 词:动态价格发现  VECM-DCC-GARCH模型  时变信息份额模型  
收稿时间:2017-12-09

Dynamic price discovery of steel trading markets in China
FANG Wen,FENG Gengzhong,LU Fengbin,WANG Shouyang.Dynamic price discovery of steel trading markets in China[J].Systems Engineering —Theory & Practice,2019,39(1):49-59.
Authors:FANG Wen  FENG Gengzhong  LU Fengbin  WANG Shouyang
Institution:1. School of Economics and Management, Xidian University, Xi'an 710126, China;2. School of Management, Xi'an Jiaotong University, Xi'an 710049, China;3. The Key Lab of the Ministry of Education for Process Control & Efficiency Engineering, Xi'an Jiaotong University, Xi'an 710049, China;4. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China
Abstract:Currently, there exists three kinds of steel trading markets in China:Spot market, futures market and B2B electronic trading market (Abbreviated as e-market). Do they reflect the steel market price common factor well? How about their dynamic evolution in terms of price discovery? These questions become hot point of steel producers, sellers, arbitrageurs, as well as market policy planners. In the light of vector error correction and conditional heteroscedasticity model, and analyzing the effects of past information to multiple dynamic conditional covariance matrix, this paper constructs time-varying information shares model based on two-dimensional and three-dimensional VECM-DCC-GARCH model to study the dynamic performance of steel markets in the long interval price discovery function. Empirical results of the daily data indicate that e-market exhibits greatest ability in incorporating information effecitively before hot roll bars futures established. After hot roll bars futures established, three kinds of steel market all contribute to the price discovery process. Most of the time, spot market leads the price discovery process, followed by the futures market and e-market. The role of e-market in price discovery is somehow considerable, while its role on price discovery evolves follower from dominator. In terms of steel markets in China, trading volume, margin level and liquidity have no obvious directly relationship with price discovery function.
Keywords:dynamic price discovery  VECM-DCC-GARCH model  time-varying information shares method  
本文献已被 CNKI 等数据库收录!
点击此处可从《系统工程理论与实践》浏览原始摘要信息
点击此处可从《系统工程理论与实践》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号