A Sales Forecasting Model for the Consumer Goods with Holiday Effects

Authors

  • Mu Zhang School of Big Data Application and Economics, Guizhou University of Finance and Economics
  • Xiaonan Huang School of Big Data Application and Economics, Guizhou University of Finance and Economics
  • Changbing Yang School of Big Data Application and Economics, Guizhou University of Finance and Economics

Keywords:

Consumer goods sales forecasting holiday effects seasonal decomposition ARIMA model seasonal factor

Abstract

In reality, there are so-called holiday effects in the sales of many consumer goods, and their sales data have the characteristics of double 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 constructed to test the holiday effects in consumer goods market. Second, using the seasonal decomposition, the seasonal factor is separated from the original series, and the seasonally adjusted series is then obtained. Through the ARIMA model, a trend forecast to the seasonally adjusted series is further carried out. Finally, according to the multiplicative model, refilling the trend forecast value with the seasonal factor, thus, the final sales forecast results of the consumer goods with holiday effects can be obtained. Taking the cigarettes sales in G City, Guizhou, China as an example, the feasibility and effectiveness of this new model is verified by the example analysis results.

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Published

2021-10-15

How to Cite

Zhang, M., Huang, X., & Yang, C. (2021). A Sales Forecasting Model for the Consumer Goods with Holiday Effects. Journal of Risk Analysis and Crisis Response, 10(2). Retrieved from https://jracr.com/index.php/jracr/article/view/122

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