基于时间序列分析的我国煤炭价格指数研究  

Research on China Coal Price Index Based on Time Series Analysis

作　　者：乔舰[1] 王禄洲 

机构地区：[1]中国矿业大学(北京)理学院,北京

出　　处：《统计学与应用》2020年第4期631-637,共7页Statistical and Application

摘　　要：本文选取中国煤炭工业协会发布的中国煤炭价格指数(CCPI)全国综合指数作为煤炭价格的研究对象,基于时间序列分析的指数平滑法、ARIMA-ARCH模型、协整–误差修正模型方法对我国煤炭价格指数进行了系统研究。研究表明我国煤炭价格指数周期性的表现在2012年前后是不同的;可预测2020年我国煤炭价格持续走低;我国煤炭价格受外在事件或政策影响反应强烈,好消息和坏消息对价格波动性的冲击等大;国际WTI原油价格的当期波动会对我国煤炭价格指数的当期波动产生显著影响,上期误差对当期波动的影响也高度显著。未来可通过使用频率更高的数据、对煤炭价格进行分时段、从全球视角等方面对我国煤炭价格指数波动做进一步研究。In this paper, China coal price index (CCPI) issued by China Coal Industry Association is selected as the research object of coal price. Based on the exponential smoothing method, ARIMA-ARCH model and cointegration-error correction model of time series analysis, this paper makes a systematic study of China coal price index. The research shows that the cyclical performance of China coal price index is different before and after 2012;It can be predicted that China’s coal price will continue to decline in 2020;China coal price is strongly, persistent and asymmetric when it is influenced by external events or policies, and the impact of good news and bad news on price volatility is equal;the current fluctuation of International WTI crude oil price will have a significant impact on the current fluctuation of China coal price index, and the error of the previous period will have a signif-icant impact on the current fluctuation. The impact of volatility is also highly significant. In the fu-ture, the China coal price index can be further studied by using more frequent data, dividing coal prices into different periods, and from a global perspective.

关 键 词：指数平滑法 ARIMA ARCH 协整检验 

分 类 号：F42[经济管理—产业经济]