A Sales Forecasting Model for the Consumer Goods with Holiday Effects

Journal of Risk Analysis and Crisis Response: JRACR

article

Mu Zhang¹  Xiao-nan Huang¹  Chang-bing Yang¹ 

[1] School of Big Data Application and Economics, Guizhou University of Finance and Economics;Guizhou Institution for Technology Innovation and Entrepreneurship Investment, Guizhou University of Finance and Economics

关键词: Consumer goods;    sales forecasting;    holiday effects;    seasonal decomposition;    ARIMA model;    seasonal factor;   

DOI  :  10.2991/jracr.k.200709.001

来源: Atlantis Press

【 摘 要 】

In reality, there are so-called holiday effects in the sales of many consumer goods, and their sales data have the characteristics ofdouble trend change of time series. In view of this, by introducing the seasonal decomposition and ARIMA model, this paperproposes a sales forecasting model for the consumer goods with holiday effects. First, a dummy variable model is constructedto test the holiday effects in consumer goods market. Second, using the seasonal decomposition, the seasonal factor is separatedfrom the original series, and the seasonally adjusted series is then obtained. Through the ARIMA model, a trend forecast to theseasonally adjusted series is further carried out. Finally, according to the multiplicative model, refilling the trend forecast valuewith the seasonal factor, thus, the final sales forecast results of the consumer goods with holiday effects can be obtained. Takingthe cigarettes sales in G City, Guizhou, China as an example, the feasibility and effectiveness of this new model is verified by theexample analysis results.

【 授权许可】

Unknown