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北美天然气现货价格波动机制分析及波动率预测 被引量:5

Analysis on the fluctuation mechanism of natural gas spot price in North America and its volatility prediction
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摘要 作为最清洁的化石能源,天然气的使用越来越广泛.然而其价格波动将影响天然气行业的投资与需求、导致生产成本管理困难并影响能源政策的制定和经济增长等.因此,充分了解天然气的价格决定机制及未来波动趋势至关重要.研究利用动态贝叶斯网络模型(dynamic Bayesian network,DBN)研究Henry Hub天然气现货价格的波动机制并预测价格波动率.作为研究结果,建立了天然气现货价格形成机制的动态因果网络图,全面展示了驱动价格形成的直接因素与间接因素.预测结果给出了未来24个月天然气现货价格波动率的取值范围及其概率,如:1、6、7、10月份,天然气现货价格将以0.2072的概率保持在[-10%,0%]的增长率水平.研究结论为天然气驱动因素的探索提供了全面的分析框架,也为投资者和政策制定者提供了更全面的预测信息. As the cleanest fossil energy,natural gas is used more and more widely.However,the price fluctuation will affect the investment and demand of natural gas industry,lead to production cost management difficulties,and affect the formulation of energy policy and economic growth.Therefore,it is very important to fully understand the price determination mechanism and future fluctuation trend of natural gas.In this paper,dynamic Bayesian network model(DBN)is used to study the volatility mechanism of Henry Hub natural gas spot price and to predict the price volatility.As a result,we establish a dynamic causal network diagram of the formation mechanism of natural gas spot price,which comprehensively shows the direct and indirect factors driving the price formation.The forecast results show the range and probability of spot price volatility of natural gas in the next 24 months.For example,in January,June,July and October,the spot price of natural gas will maintain a growth rate of[-10%,0%]with a probability of 0.2072.Our research provides a comprehensive analysis framework for exploring the driving factors of natural gas,and also provides more comprehensive prediction information for investors and policy makers.
作者 史惠婷 柴建 卢全莹 汪寿阳 SHI Huiting;CHAI Jian;LU Quanying;WANG Shouyang(School of Economics and Management,University of Chinese Academy of Sciences,Beijing 100190,China;School of Economics and Management,Xidian University,Xi'an 710071,China;Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190,China)
出处 《系统工程理论与实践》 EI CSSCI CSCD 北大核心 2021年第12期3366-3377,共12页 Systems Engineering-Theory & Practice
基金 国家自然科学基金(71874133) 陕西省“高层次人才特殊支持计划”青年拔尖人才 中国博士后科学基金(2020M680719)。
关键词 天然气现货价格 驱动因素分析 波动率预测 动态贝叶斯网络模型 natural gas spot price driving factor analysis price prediction dynamic Bayesian network model
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