期刊文献+

基于VAR-DCC-GARCH模型的国内外有色金属商品价格联动分析(英文) 被引量:16

Price linkage between Chinese and international nonferrous metals commodity markets based on VAR-DCC-GARCH models
下载PDF
导出
摘要 运用VAR-DCC-GARCH模型,研究LME金属价格与中国金属价格间的联动效应及其动态相关性。结果表明:LME金属价格依然对中国金属价格有着较大的影响,而中国除了铅价外,其余金属价格对LME金属价格的影响还很微弱;中国铜、铅、锌价格与LME价格间均存在正向的联动性;LME金属价格与中国金属价格之间的联动性在反应时间上存在滞后性,滞后期在7到8个交易日左右;LME金属价格和中国金属价格间的互动影响关系存在时变性,其中,LME铅价与中国铅价间的相互关联最稳定。 Using VAR-DCC-GARCH model,the literature on commodity price was extended by exploring the co-movement between Chinese nonferrous metal prices and global nonferrous metal prices represented by the nonferrous metal prices from London Metal Exchange(LME).The results show that LME nonferrous metals prices still have a greater impact on Chinese nonferrous metals prices.However,the impact of Chinese nonferrous metals prices on LME nonferrous metals prices is still weak except for lead price.The co-movement of nonferrous metal prices between LME and China presents hysteretic nature,and it lasts for 7-8trading days.Furthermore,the co-movement between LME nonferrous metals prices and Chinese nonferrous metals prices has the characteristics of time-varying,and the correlation of lead prices between LME and China is the more stable than all other nonferrous metals prices.
出处 《Transactions of Nonferrous Metals Society of China》 SCIE EI CAS CSCD 2015年第3期1020-1026,共7页 中国有色金属学报(英文版)
基金 Project(71073177)supported by the National Natural Science Foundation of China Project(12JJ4077)supported by the Natural Science Foundation of Hunan Province of China Project(2012zzts002)supported by the Fundamental Research Funds of Central South University,China
关键词 价格联系 有色金属商品价格 中国金属商品市场 伦敦金属交易所 联动性 VAR模型 DCC-GARCH price linkage nonferrous metals commodity prices Chinese metals commodity market LME co-movement VAR model DCC-GARCH model
  • 相关文献

参考文献11

  • 1程慧,黄健柏,郭尧琦,朱学红.基于分形特征的金属期货量价相关性的长记忆性(英文)[J].Transactions of Nonferrous Metals Society of China,2013,23(10):3145-3152. 被引量:3
  • 2Joseph P. Byrne,Giorgio Fazio,Norbert Fiess.Primary commodity prices: Co-movements, common factors and fundamentals[J]. Journal of Development Economics . 2013
  • 3Anshul Jain,Sajal Ghosh.Dynamics of global oil prices, exchange rate and precious metal prices in India[J]. Resources Policy . 2012
  • 4Ramazan Sari,Shawkat Hammoudeh,Ugur Soytas.Dynamics of oil price, precious metal prices, and exchange rate[J]. Energy Economics . 2009 (2)
  • 5On the excess co-movement of commodity prices—A note about the role of fundamental factors in short-run dynamics[J]. Energy Policy . 2009 (10)
  • 6Robert Engle.Dynamic Conditional Correlation[J]. Journal of Business & Economic Statistics . 2002 (3)
  • 7C. ciner.On the long run relationship between gold and silver prices A note[J]. Global Finance Journal . 2001 (2)
  • 8Brian M. Lucey,Edel Tully.The evolving relationship between gold and silver 19782002: evidence from a dynamic cointegration analysis: a note. Applied Financial Economics Letters . 2006
  • 9P.Cashin,H.Liang,McDermott,C.J.How Persistent are Shocks to World Commodity Prices. IMF Working Paper . 1999
  • 10Andr Varella Mollick,Joo Ricardo Faria,Pedro H. Albuquerque,Miguel A. Len-Ledesma.Can globalisation stop the decline in commodities’ terms of trade?. Cambridge Journal of Economics . 2008

二级参考文献21

  • 1BOLLERSLEV T, JUB1NSKI D. Equity trading volume and volatility: Latent information arrivals and common long-run dependencies [J]. Journal of Business & Economic Statistics, 1999, 17(1): 9-21.
  • 2LAMOUREUX C, LASTRAPES W D. Endogenous trading volume and momentum in stock return volatility [J]. Journal of Business & Economic Statistics, 1994, 12(2): 253-260.
  • 3LOBATO I N. Long memory in stock market trading volume [J]. Journal of Business & Economic Statistics, 2000, 18(4): 410-427.
  • 4PANAS E. Long memory and chaotic models of prices on the London metal exchange [J]. Resources Policy, 2001, 27(4): 235-246.
  • 5ALVAREZ J R, CISNEROS M, IBARRA C V, SORIANO A. Multifractal Hurst analysis of crude oil prices [J]. Physica A, 2002, 313(3-4): 651-670.
  • 6SERLETIS A, ANDREADIS L. Random fractal structures in north American energy markets [J]. Energy Economics, 2004, 26(3): 389-399.
  • 7TABAK B M, CAJUEIRO D O. Are the crude oil markets becoming weakly efficient over time? A test for time-varying long-range dependence in prices and volatility [J]. Energy Economics, 2007, 29(1): 28-36.
  • 8POWER G J, TURVEY C G. Long-range dependence in the volatility of commodity futures prices: Wavelet-based evidence [J]. Physica A, 2010, 389(1): 79-90.
  • 9WANG Y, WEI Y, WU C. Auto-correlated behavior of WTI crude oil volatilities: A multiscale perspective [J]. Physica A, 2010, 389(24): 5759 5768.
  • 10JIA Z, CUI M, LI H. Research on the relationship between the multifractality and long memory of realized volatility in the SSECI [J]. Physica A, 2012, 391(3): 740-749.

共引文献4

同被引文献194

引证文献16

二级引证文献36

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部