Crude oil is a commodity with both strategic and financial attributes, and its financial attribute affects its price fluctuation to the commodity futures market inevitably. Scholars through the world have studied the impact of crude oil on non energy markets such as food and agricultural products. However, little literature has been done to study the risk conduction relationship between international crude oil and Chinese commodity futures market from risk view.
This paper studies the influence of international crude oil price fluctuation on commodity futures in different historical stages, using the correlation structure breakpoint method proposed by Wied and Kramer(2012, Econometric Theory). The price trend is divided into three historical stages of international crude oil's impact on commodity futures. And the model of risk conduction proposed by Adam and Gluck(2015, Journal of Banking & Finance) is used to study the impact of international crude oil price fluctuation on Chinese commodity futures.
The empirical analysis of three types representative commodity futures, such as rubber, copper and agricultural products from January 2001 to May 2017, is selected. On one hand, the influence of international crude oil to these commodities is clearly divided into three sections by using the correlation structure breakpoint method. The results are as follows:in the first section from 2001-2008, the correlation is maintained below 0.05; in the second section from 2008-2014, the correlation increases to more than 0.22; while in the third section from 2014-2017, the correlation falls below 0.06. The correlation between China's commodity futures and international crude oil has been found cyclical, with a cycle of about seven years. On the other hand, the risk conduction model is used to study the impact of international crude oil on the three commodity futures in three historical sections. The result shows that the correlation between the period of 2008-2014 is easily founded; from the perspective of risk conduction, effect of three futures and the international crude oil have obvious difference and regularity, especially in the high correlation period, the risk conduction trend from high to low showing a "ladder" change, similarly. The conclusion above is not only beneficial to the entity operators to recognize the possible risks from the macro perspective, but also to provide a useful policy basis for the financial supervision department.
LIU Ying-lin, LIU Yong-hui, JU Zhuo
. The Impact of International Crude Oil Price Fluctuation on Chinese Commodity Futures——Based on the Correlation Structure Breakpoint Model[J]. Chinese Journal of Management Science, 2019
, 27(2)
: 31
-40
.
DOI: 10.16381/j.cnki.issn1003-207x.2019.02.004
[1] Basak S, Pavlova A. A model of financialization of commodities[J]. Journal of Finance, 2016, 71(4):1511-1555.
[2] Adams Z, Glück T. Financialization in commodity markets:A passing trend or the new normal?[J]. Journal of Banking & Finance, 2015, 60:93-111.
[3] 韩立岩, 尹力博. 投机行为还是实际需求?——国际大宗商品价格影响因素的广义视角分析[J]. 经济研究, 2012, (12):83-96.
[4] 尹力博, 柳依依. 中国商品期货金融化了吗?——来自国际股票市场的证据[J]. 金融研究, 2016,(3):189-206.
[5] 刘映琳,鞠卓,刘永辉. 基于DCC-GARCH的中国大宗商品金融化研究[J]. 国际商务研究, 2017, (5), 75-83.
[6] Tang Ke, Xiong Wei. Index investment and the financialization of commodities[J]. Financial Analysts Journal, 2012, 68(6):54-74.
[7] Zhang Chuanguo, Qu Xuqin. The effect of global oil price shocks on China's agricultural commodities[J].Energy Economics, 2015, 51:354-364.
[8] Ji Qiang, Fan Ying. How does oil price volatility affect non-energy commodity markets?[J]. Applied Energy, 2012, 89(1):273-280.
[9] Marcellino M, Sivec V. Monetary, fiscal and oil shocks:Evidence based on mixed frequency structural FAVARs[J]. Journal of Econometrics, 2016, 193(2):335-348.
[10] Cross J, Bao H N. The relationship between global oil price shocks and China's output:A time-varying analysis[J]. Energy Economics, 2016, 62:79-91.
[11] Kim W J, Hammoudeh S, Hyun J S, et al. Oil price shocks and China's economy:Reactions of the monetary policy to oil price shocks[J]. Energy Economics, 2017,62:61-69.
[12] 吴振信, 薛冰, 王书平. 基于VAR模型的油价波动对我国经济影响分析[J]. 中国管理科学, 2011, 19(1):21-28.
[13] 张程, 范立夫. 大宗商品价格影响与货币政策权衡——基于石油的金融属性视角[J]. 金融研究, 2017, (3):72-85.
[14] 姬强, 范英. 次贷危机前后国际原油市场与中美股票市场间的协动性研究[J]. 中国管理科学, 2010, 18(6):42-50.
[15] 董坤, 谢海滨, 汪寿阳. 中国股票市场的石油效应之谜[J]. 管理科学学报, 2012, 15(11):45-53.
[16] 李素芳, 朱慧明, 李荣. 基于贝叶斯机制转换协整模型的石油——股市非对称效应研究[J]. 中国管理科学, 2015, 23(9):46-54.
[17] Salisu A A, Fasanya I O. Modelling oil price volatility with structural breaks[J]. Energy Policy, 2013, 52(1):554-562.
[18] 柴建, 卢全莹, 周友洪,等. 国际原油价格拐点分析及统计推断[J]. 中国管理科学, 2017, (5):33-41.
[19] 林伯强, 李江龙. 原油价格波动性及国内外传染效应[J]. 金融研究, 2012, (11):1-15.
[20] 王璐, 黄登仕, 乔高秀,等. 突变结构下国际石油价格对中国股市影响的局部相关性[J]. 系统工程, 2016,(10):1-10.
[21] Liu Yonghui, Ji Guocheng,Liu Shuangzhe. Influence diagnostics in a vector autoregressive model[J]. Journal of Statistical Computation and Simulation, 2015,85(13):2632-2655.
[22] Liu Yonghui, Sang Ruochen,Liu Shuangzhe. Diagnostic analysis for a vector autoregressive model under student t-distribution[J], Statistica Neerlandica, 2017, 71(2):86-114.
[23] 张翔, 刘璐, 李伦一. 国际大宗商品市场金融化与中国宏观经济波动[J]. 金融研究, 2017, (1):35-51.
[24] 钟美瑞, 谌杰宇, 黄健柏,等. 基于MSVAR模型的有色金属价格波动影响因素的非线性效应研究[J]. 中国管理科学, 2016, 24(4):45-53.
[25] Avalos F. Do oil prices drive food prices? The tale of a structural break[J]. Journal of International Money & Finance, 2014, 42(42):253-271.
[26] Cheng I H, Xiong Wei. Financialization of commodity markets[J]. Annual Review of Financial Economics, 2014,6:419-441.
[27] Wied D, Kramer W. Testing for a change in correlation at an unknown point in time using an extended functional delta method[J]. Econometric Theory, 2012,28(3):570-589.
[28] Galeano P, Wied D. Multiple break detection in the correlation structure of random variables[J]. Computational Statistics and Data Analysis, 2014,76:262-282.
