消费者信心指数的研究
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摘要
本文利用我国台湾省连续十年的月度消费者信心指数数据,通过对信心指数时间序列的分析,探讨了六项分指数间的变化规律。
文中首先采用了探索性数据分析方法,描述六项分指数序列的基本变化形态,进而采用时间序列挖掘和经典的模型相结合的方法来分析六项分指数的变化特点。在应用时间序列相似性检索的过程中,本文创造性的提出了界标点模式距离法用以测算时间序列的相似性。
通过时间序列的关联规则挖掘和相似性检索发现,各序列间家庭经济和地区经济的关系最为紧密,其变化模式最为接近。投资项分指数的变化模式有别于其他序列,而且购买项分指数也显示出独特的变化特点。
通过对信心指数六项分指数的ARIMA模型、VAR模型分析,发现各分指数主要受自身滞后一期影响最大。投资项分指数明显区别于其他几个分项指数,投资项分指数接近于随机游走模型。
论文最大的成果在于通过对六项分指数的深入研究,给出信心指数编制、使用的建议。在信心指数的编制和发布时,正确处理各分项指数的影响作用。
In this paper, Time series of Consumer Confidence Index,ten years of monthly consecutive data of China's Taiwan province,were used to explore the variation correlation among the six sub-indexes.
Firstly, by descriptive statistics, the paper describe the fundamental changes to the form of six sub-index sequences, and then using a combination of the classic model of analysis and time series mining to analyze the changes in the characteristics of the six sub-indexes. Of time series similarity search process, the crucial-boundary-point was found to calculate the distance of two time series when to look for the similarity of them, the method which was used to calculate the distance was a new trail of this paper.
Second, found by association rule mining of time series and similarity search, Family Economy sub-index and Regional Economy sub-index is most closely related to each other, the change patterns of this two series is the closest among all of the six indexes. The change pattern of the Investment sub-index is different from other sequences, and Purchase sub-index also shows the unique characteristics.
Last, through six sub-indices of the confidence index of the ARIMA model, VAR model analysis, the author found that the sub-index is mainly affected by its own one-month-lag impact. The Investment sub-index significantly different from several other sub-indexes, the Investment sub-index is close to the Random Walk Model.
The significant results of the paper is giving the in-depth study of the six sub-indexes, and giving the recommendations of the survey and construction of the six indexes.
文中首先采用了探索性数据分析方法,描述六项分指数序列的基本变化形态,进而采用时间序列挖掘和经典的模型相结合的方法来分析六项分指数的变化特点。在应用时间序列相似性检索的过程中,本文创造性的提出了界标点模式距离法用以测算时间序列的相似性。
通过时间序列的关联规则挖掘和相似性检索发现,各序列间家庭经济和地区经济的关系最为紧密,其变化模式最为接近。投资项分指数的变化模式有别于其他序列,而且购买项分指数也显示出独特的变化特点。
通过对信心指数六项分指数的ARIMA模型、VAR模型分析,发现各分指数主要受自身滞后一期影响最大。投资项分指数明显区别于其他几个分项指数,投资项分指数接近于随机游走模型。
论文最大的成果在于通过对六项分指数的深入研究,给出信心指数编制、使用的建议。在信心指数的编制和发布时,正确处理各分项指数的影响作用。
In this paper, Time series of Consumer Confidence Index,ten years of monthly consecutive data of China's Taiwan province,were used to explore the variation correlation among the six sub-indexes.
Firstly, by descriptive statistics, the paper describe the fundamental changes to the form of six sub-index sequences, and then using a combination of the classic model of analysis and time series mining to analyze the changes in the characteristics of the six sub-indexes. Of time series similarity search process, the crucial-boundary-point was found to calculate the distance of two time series when to look for the similarity of them, the method which was used to calculate the distance was a new trail of this paper.
Second, found by association rule mining of time series and similarity search, Family Economy sub-index and Regional Economy sub-index is most closely related to each other, the change patterns of this two series is the closest among all of the six indexes. The change pattern of the Investment sub-index is different from other sequences, and Purchase sub-index also shows the unique characteristics.
Last, through six sub-indices of the confidence index of the ARIMA model, VAR model analysis, the author found that the sub-index is mainly affected by its own one-month-lag impact. The Investment sub-index significantly different from several other sub-indexes, the Investment sub-index is close to the Random Walk Model.
The significant results of the paper is giving the in-depth study of the six sub-indexes, and giving the recommendations of the survey and construction of the six indexes.
引文
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