主管:中国科学院
主办:中国优选法统筹法与经济数学研究会
   中国科学院科技战略咨询研究院

中国管理科学 ›› 2018, Vol. 26 ›› Issue (11): 42-49.doi: 10.16381/j.cnki.issn1003-207x.2018.11.005

• 论文 • 上一篇    下一篇

中国原油期货动态风险溢出研究

张大永1, 姬强2,3   

  1. 1. 西南财经大学经济与管理研究院, 四川 成都 611130;
    2. 中国科学院科技战略咨询研究院能源与环境政策研究中心, 北京 100190;
    3. 中国科学院大学公共政策与管理学院, 北京 100049
  • 收稿日期:2017-08-14 修回日期:2018-08-14 出版日期:2018-11-20 发布日期:2019-01-23
  • 通讯作者: 姬强(1982-),男(汉族),山东威海人,中国科学院科技战略咨询研究院副研究员,研究方向:能源金融、能源安全战略管理,E-mail:jqwxnjq@163.com. E-mail:jqwxnjq@163.com
  • 基金资助:

    国家自然科学基金资助项目(71774152,71573214,91546109);中国科学院青促会项目(Y7X0231505)

Studies on the Dynamic Risk Spillovers for China's Crude Oil Futures

ZHANG Da-yong1, JI Qiang2,3   

  1. 1. Research Institute of Economics and Management Southwestern University of Finance and Economics, Chengdu 611130, China;
    2. Center for Energy and Environmental Policy Research, Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China;
    3. School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2017-08-14 Revised:2018-08-14 Online:2018-11-20 Published:2019-01-23

摘要: 本文首次量化分析了我国原油期货与国际基准原油、上证指数以及人民币汇率之间的风险溢出关系。通过构建收益率和波动率的静态和动态网络,本文对我国原油期货与国内外市场之间的信息流向的强度、方向和动态性进行了初步的探索。研究发现,我国上市的原油期货与国际基准原油之间的信息关联密切,与股票市场以及汇率市场之间的关系相对较弱。同时,在构建的原油-股票-汇率系统中,我国原油期货处于信息的接收方,国际油价波动信息对我国原油期货市场存在明显的正向冲击作用。

关键词: 上海原油期货, 风险溢出, 联接网络

Abstract: Risk spillovers among Shanghai crude oil futures, international crude oil prices, Shanghai stock market index and RMB exchange rate are empirically investigated in this paper. Based on constructing of static and dynamic networks for returns and volatilities, the paper allows us to gather first-hand information on how Shanghai crude oil futures interacts with domestic and international markets. Results demonstrate a strong linkage between crude oil futures and international oil market, however, the interaction with financial markets are relatively weak. Meanwhile, Shanghai crude oil futures has shown to be a net information receiver in the system. Variations in the international crude oil markets have significant impact to this newly introduced oil futures.
As crude oil remains the most important energy resource world wide, its price dynamics have had significant impacts on all aspects of the global economy. One of the most exciting changes of the energy market in recent years is its financialization process. This newly developed phenomenon has generated new features of the market and also brings challenges to both practitioners and academia, where there has emerged a fast growing body of literature studying the energy market under the broad concept of energy finance.
One most notable event in the global energy market is that China launched its first crude oil futures contract in Shanghai Futures Exchange on 26 March 2018. Its trading volume soon exceeded that of Omen crude oil futures, making it world's third major crude oil futures. While its success has given investors new opportunities, the associated risk control/management has become an increasing concern. It is urgent and important to understand how much crude oil futures interacts with the financial markets and provide first hand empirical evidence.
A systemic approach proposed by Diebold and Yilmaz (2009, 2014) is adopted and a four-variable vector autoregressive (VAR) model that includes crude oil futures, international benchmark oil prices, stock market index and foreign exchange rate is established. The model is applied to both returns and volatilities of the underlying variables. Using the generalized forecasting error decomposition (FEVD) technique, which helps avoid the problems of ordering in the VAR model, we are able to explicitly identify how much the system is interacted and show directly the spillover (information) effects among variables. To accommodate the possible time-varying feature, a rolling-windows approach is also applied to show the dynamic nature of this system. The modelling strategy has been proved to be an effective way in discovering risk spillovers across different markets.
The data used in this paper are collected from the WIND finance database. The Shanghai crude oil futures price (INE), WTI (Brent price for robustness check) crude oil prices, RMB/US dollar exchange rate and Shanghai composite index are used for the empirical analysis. All data are from 26/03/2018 to 31/07/2018 in daily frequency. From the descriptive statistics, it is clearly spotted that international oil prices have the highest volatility, which is followed by Shanghai crude oil futures. The pattern reflects the complications of the recent international environment and further motivated us to study risk spillovers between China and the international markets.
The main findings of this paper can be summarized as the following key points:first, we provide first-hand empirical evidence is provided that the newly launched Shanghai crude oil futures have close links with the international crude oil market, and it is a net information receiver. For example, the net explanatory power of WTI price changes to the Shanghai crude oil futures is 42.1%. It indicates that the crude oil market is still dominated by the international benchmark, whilst China's crude oil futures market has a long way to go to have real impacts on the global market. Second, the interactions between crude oil futures and the financial market are marginal. It is consistent with the existing literature that China has limited impacts on international crude oil market. The new crude oil futures market is yet to develop to become a key financial instrument. Third, clear evidence of time-varying relationships is found.
Although the sample covers only four months, the global political/economic environment experienced dramatic changes during this particular period. The China-US trade conflict, the middle-east turmoil and general uncertainties in the global economy have made the international crude oil market more volatile and complicated. Our empirical study makes timely and importantcontributions to guiding further actions of risk management and control. This includes helping investors to form optimal investment strategies taking into account risk spillovers across markets, as well as policy makers to understand the dynamic patterns of the crude oil future market.

Key words: Shanghai crude oil futures, risk spillover, connectedness network

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