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李剑1 李崇光1


【摘要】本文引入价格泡沫理论与分析方法, 提出了基于价格泡沫视角的农产品期货市场风险评价方法和分析框架, 创建了“泡沫长度”“泡沫频度”“泡沫强度”3个风险评价指标, 对2006~2014年中国农产品期货市场历史风险水平进行了测量和评价。依据风险评价结果, 本文将10种主要农产品期货品种划分为高、中、低3个风险等级, 并总结出各个风险等级商品的风险特征和调控启示。本文的研究结果显示, 商品功能属性不能完全显示商品风险属性, 有必要按照“分级监控、重点防范”的原则, 完善农产品期货市场风险监管体系。

【关键词】 农产品期货市场;风险评价;价格泡沫;右尾单位根检验;


【基金资助】 国家自然科学基金项目“‘金融化’背景下中国农产品期货与现货市场风险评价与传导研究” (项目编号:71673103) 的阶段性成果;

Risk assessment of agricultural futures markets: a new analysis framework based on price bubble model

LI Jian 1 LI Chongguang1

(1.College of Economics & Management, Huazhong Agricultural University)

【Abstract】This paper introduced price bubble theory and its analysis method, suggested the assessment method and analysis framework of agricultural commodity futures market risk from the perspective of price bubble, set three risk assessment indexes including “bubble duration”, “bubble frequency” and “bubble intensity”, and conducted measurement and assessment of the historical risk levels of China’s agricultural commodity futures market during 2006-2014. According to the risk assessment results, this paper divided agricultural commodity futures products into high, middle and low levels in risk and summarized the risk features and control implications of the commodities at each risk level. The research results of this paper show that commodity function cannot completely reflect its risk attribute, so it is necessary to complete the risk regulating system of agricultural commodity futures market in the principle of “monitoring by level and preventing by priority.”

【Keywords】 agricultural futures market; risk assessment; price bubble; right-tail unit root test;


【Funds】 National Natural Science Foundation of China (71673103);

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    [1]. ① Source: [^Back]

    [2]. ① Source: The data are processed by the authors according to those from, and [^Back]

    [3]. ② In this paper, the “risk assessment” of agricultural commodity futures market refers to risk measurement and assessment of the historical price series of commodities, including three parts: (1) bubble test of historical data; (2) risk rating of commodities according to risk assessment indexes; and (3) summary of risk features and regulating means of commodities at different risk levels. [^Back]

    [4]. ① Some concepts, quite new in this paper, have no unified translation yet in the domestic academic circle in China, so the authors translated them and noted them with original English versions. For any improperness, readers’ correction is welcome. Also, see Jian and Xiang (2012) and Deng (2013) for reference. [^Back]

    [5]. ② PSY is the initials of Phillips et al. (2015). [^Back]

    [6]. ① Window series refers to the observation value series adopted by each calculation of ADF values in recursive regression. It is noteworthy that PSY model needs to set initial window series, so recursive regression may have an initial sample size. The start of initial window series is the sample start, and its end is set as r0. [^Back]

    [7]. ② The CV adopted by this paper was obtained by Monte Carlo simulation for 2000 times. It is the same below without separate note. [^Back]

    [8]. ① Paddy rice (early indica rice) and canola oil contracts were listed on April 20, 2009 and July 2, 2007. By the end of 2014, there were 1386 and 1826 samples respectively. These two agricultural commodities were also included in the research due to their important research significance and relatively more sample days. [^Back]

    [9]. ② [^Back]

    [10]. ③ [^Back]

    [11]. ④ [^Back]

    [12]. ① In practice, the “comprehensive assessment” of market risk may also have different weights set over the three risk indexes, namely bubble duration, bubble frequency and bubble intensity, according to market experience and specific situations and then conduct finer analysis and assessment of the historical risk levels of agricultural commodity futures market. [^Back]


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This Article


CN: 11-1262/F

Vol , No. 05, Pages 73-87

May 2017


Article Outline


  • 1 Introduction
  • 2 Modeling
  • 3 Research data
  • 4 Risk assessment of agricultural commodity futures market
  • 5 Conclusion and discussion
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