时间序列分析在CPI中的应用研究

Application Research of Time Series Analysis in the CPI

在金融数据分析中，居民消费物价指数CPI，是衡量物价水平的重要指标，特别是衡量一国通货膨胀的程度，因此准确预测CPI未来的走势就非常重要。本文通过对经典时间序列分析方法的研究，发现是建立在一定的假设的基础上，而CPI数据通常不能完全满足这些假设，把傅里叶变换和小波分析引入到对时间序列数据的处理上，对数据进行分解和重构，结合经典的时间序列模型进行预测，并对引入后与不引入进行比较，进而得出预测精度较高的模型。

In the analysis of financial data, the consumer price index CPI is an important measure of the price level, especially to measure the extent of a country＇s inflation, thus accurately predicts the future trend of CPI is very important. Through the study of the classical time series analysis method and found to be built on the basis of certain assumptions, while the CPI data usually does not meet these assumptions, the Fourier transform and wavelet analysis is introduced to the time series data processing, data decomposition and reconstruction, combined with classical time series forecasting model, and compared the fore-and-aft introduction of wavelet analysis, and then come to a high prediction accuracy of the model