基于ARIMA-Holt指数平滑模型的短期居民消费指数预测

Short-Term Consumer Index Prediction Based on ARIMA-Holt Index Smoothing Model

摘要: 以上海市2008~2017年10年间居民消费指数(CPI)的月度历史数据为样本，采取时间序列检验方法对其进行了相关分析，建立了ARIMA模型。同时利用多种不同预测方法对2018年第一季度上海市居民消费指数水平进行预测，结果表明：上海市居民消费指数具有明显的趋势性，且Holt指数平滑预测方法具有更优的预测能力，效果较为理想，为短期预测提供一定的借鉴。

Abstract: Taking the monthly historical data of Shanghai Consumer Price Index (CPI) for the 10-year period from 2008 to 2017 as a sample, the time series test method was used to analyze the correlation and establish the ARIMA model. At the same time, a variety of forecasting methods are used to forecast the level of Shanghai Residents’ consumption index in the first quarter of 2018. The results show that the Shanghai consumer index has a clear trend, and the Holt index smooth forecasting method has better forecasting ability, and the effect is ideal, which provides a certain reference for short-term forecasting.