摘要
石油作为影响全球经济发展的重要因素,其价格的波动受到多种因素的影响。为了全面地识别石油市场风险及其动态演化过程,本文利用爬虫技术抓取网络信息,经过文本预处理等操作,建立矩阵分解石油风险模型(Matrix Factorization for oil risk model,MFORM)。实证结果表明,MFORM不仅能准确地识别石油市场的供需基本面因素,也能鉴识期货市场、地缘政治、金融市场等非基本面的因素,同时可以分析石油市场风险的动态演变过程,描述风险的时效性,为进行石油市场风险管理,建立石油市场风险预测预警机制提供了有效的工具。
As an important factor affecting the development of the global economy, the fluctuation among oil prices is affected by many factors. To comprehensively identify risk in oil market and its dynamic evolution process, this paper utilizes crawler technology to captures network information, and performs text preprocessing steps to establish a matrix factorization for oil risk model (MFORM). The empirical results show that the MFORM can not only accurately identify the supply and demand fundamental factors in oil market, but also non-fundamental factors such as futures market, geopolitics, and US dollar exchange rate. At the same time, the MFORM can analyze the dynamic evolution process of oil market risk, describe the timeliness of the risk, and provide an effective tool for oil market risk management and establishing the risk forecasting and early warning mechanism in oil market.
出处
《中国能源》
2019年第6期16-19,26,共5页
Energy of China
基金
国家自然科学基金项目(编号:71871020,71403014,71521002)
关键词
风险识别
石油市场
矩阵分解
文本挖掘技术
Risk Identification
Oil Market
Matrix Factorization
Text Mining Technology