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作 者:雷强
机构地区:[1]神华科学技术研究院发展战略研究所,北京102211
出 处:《资源科学》2013年第10期1968-1976,共9页Resources Science
基 金:世界煤炭协会(WCA)和神华集团国际合作研究项目--2013年科技创新项目之重大宏观战略研究课题"未来世界煤炭工业发展趋势研究"(项目编号:YJY-1)的阶段性研究成果
摘 要:煤炭是全球基础性能源和战略资源,特别是在以煤炭为主要能源消费的我国,煤炭价格分析是我国经济发展研究中至关重要的问题之一。本文利用BDS法和替代数据法对我国两种煤炭价格(秦皇岛大同优混(Q5800K)和山西优混(Q5500K))和国外煤炭价格(澳大利亚BJ动力煤现货价)进行了深入研究。研究表明,3种煤炭价格收益率序列不服从正态分布,存在长相关特征并具有非线性结构。国外煤炭价格的非线性特征较国内煤炭价格非线性要强,表明国际煤炭市场的影响因素比国内煤炭市场更加复杂,市场化程度更高。在替代数据法检验时发现在嵌入维数大于5时,上述价格原始数据和替代数据均有显著性差异,表明影响国内外煤炭价格的主要因素至少5个,说明可以建立5维非线性模型进行短期预测,为我国煤炭政策制定及煤炭行业科学发展提供理论指导。As the world's basic energy source important issue in the economic development of and strategic resource, coal price analysis is an coal-dominated countries such as China. Based on the BDS method and the surrogate data method, we studied the nonlinear characteristics of domestic coal prices at Qinhuangdao Datong Hunyou (Q5800K), Qinhuangdao Port Shanxi Hunyou (Q5500K) and the Australia BJ thermal coal price. The results show that the return series of the three sets of data do not follow a normal distribution, and show fat-tailedness characteristics, have non-linear relationships and some non-linear structure. The BDS statistics of the Australian BJ thermal coal price are greater than Qinhuangdao Datong Htmyou (Q5800K) and Qinhuangdao Port Shanxi Hunyou (Q5500K), which means that the nonlinear characteristics of the Australia BJ thermal coal price are relatively stronger. The nonlinear characteristics of the foreign coal price are stronger relative to nonlinear characteristics of the domestic coal prices, which means factors affecting the international coal market are more complex and more market-oriented in comparison with the domestic coal market. In the surrogate data test, the results show that when the embedding dimension is greater than five, there is a strong difference among the original data and surrogate data of the three domestic and international coal prices, which means that the study may nonlinearly simulate the three domestic and international coal prices with at least five economic variables in order to make the short-term forecast of the coal prices, and provide theoretical guidance towards Chinese coal policy formulation and scientific development of the coal industry.
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