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 ›› 2017, Vol. 25 ›› Issue (5): 33-41.doi: 10.16381/j.cnki.issn1003-207x.2017.05.005

• 论文 • 上一篇    下一篇

国际原油价格拐点分析及统计推断

柴建1, 卢全莹2, 周友洪3, 邢丽敏4, 汪寿阳2   

  1. 1. 西安电子科技大学经济与管理学院, 陕西 西安 710126;
    2. 中国科学院大学经济与管理学院, 北京 100190;
    3. 陕西师范大学国际商学院, 陕西 西安 710062;
    4. 湖南大学工商管理学院, 湖南 长沙 410082
  • 收稿日期:2016-03-23 修回日期:2016-07-31 出版日期:2017-05-20 发布日期:2017-08-26
  • 通讯作者: 卢全莹(1991-),女(汉族),天津武清人,中国科学院大学经济与管理学院,博士生,研究方向:能源金融、能源经济、宏观经济分析与建模、预测,E-mail:luquanying0705@163.com. E-mail:luquanying0705@163.com
  • 基金资助:

    国家自然科学基金面上项目(71473155);陕西师范大学中央高校特别资助项目(14SZTZ03);陕西省青年科技新星计划项目(2016KJXX-14);西安电子科技大学2016年度基本科研业务费自由控索类项目(JB160603)

Analysis and Statistical Inference of Crude Oil Price Change Points

CHAI Jian1, LU Quan-ying2, ZHOU You-hong3, XING Li-min4, WANG Shou-yang2   

  1. 1. School of Economics and Management, Xidian University, Xi'an 710126, China;
    2. School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China;
    3. International Business School, Shanxi Normal University, Xi'an 710062, China;
    4. Business School, Hunan University, Changsha 410082, China
  • Received:2016-03-23 Revised:2016-07-31 Online:2017-05-20 Published:2017-08-26

摘要: 原油具有战略和金融双重属性。原油价格波动分析一直是全球的研究热点,特别是油价大幅波动的拐点对能源金融行业的相关人员至关重要。基于此,本文对国际原油价格拐点分析及统计推断进行了探索性研究,以原油月度价格作为研究对象,集成构建PPM-KM国际原油价格拐点分析模型以适应国际原油价格拐点后验概率的测算、聚类及识别。首先,基于PPM模型测算出国际原油价格序列突变的后验概率,并结合K-Means聚类方法给出原油价格突变后验概率识别阈值,对原油价格的历史突变进行识别和分析。其次,以比较符合描述突变规律的泊松分布,对数-正态分布,幂律分布三种分布,构建国际原油价格拐点统计推断模型,对原油月度价格的突变规律进行概率模拟并比较分析。结果表明,1986年-2015年期间共发生37次显著的油价突变。在不同的时点,市场供需结构的失衡、突发地缘政治事件、美元指数、全球经济发展情况分别成为油价突变的主因。通过对油价突变点时间间隔的分布拟合,本文初步认为国际原油月度价格拐点的时间间隔服从幂律分布的假设是合理的。

关键词: 原油价格, 拐点, PPM, K-Means聚类, 幂律分布

Abstract: The crude oil is of dual attributes, strategic and financial. Oil price fluctuations attract attention around the world, especially the oil price fluctuation change point is considered more important for energy finance industry. Based on this idea, an exploratory research direction is introduced in this paper. Monthly international crude oil prices were taken as the study objective and the PPM-KM integration model was established by extending product partition model (PPM) to adapt to measure, cluster, and identify the posterior probability of change points of international crude oil price. First, this paper measured the mutations posteriori probability of the oil price based on the PPM model in order to distinguish and analyze the mutations of the oil price, and gave the result of the tolerance threshold and mutations of commodity price combined with K-Means clustering method. Second, the Poisson distribution, power-law distribution, and logarithmic-normal distribution were used to build statistical inference model to the catastrophes description, and then corresponding probability distribution functions for simulation and analyses of the monthly crude oil price change point trends were constructed. The results showed that there were 37 significant breaking points in the period of 1986 to 2015. At different time points, the imbalanced structure of market supply and demand, unexpected events, the dollar index, the global geopolitical economic development situation the main oil mutations as the main cause of crude oil price fluctuation respectively. By fitting the distribution of the time interval of change points, this paper preliminary think the time interval of monthly international crude oil price change points obeys power-law distribution assumption is reasonable.

Key words: crude oil price, change point, PPM, K-Means, power-law distribution, Poisson distribution, logarithmic-normal distribution

中图分类号: