The application of ARIMA model in retailing industry and forecasting on economic trend of industry

Yi Lu; Zihan Wang; Yihan Wang

doi:10.1117/12.2646621

23 August 2022 The application of ARIMA model in retailing industry and forecasting on economic trend of industry

Yi Lu, Zihan Wang, Yihan Wang

Proceedings Volume 12330, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022); 1233019 (2022) https://doi.org/10.1117/12.2646621
Event: International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022), 2022, Huzhou, China

Abstract

The COVID-19 pandemic has severely impacted our lives, and many industries are experiencing instability. We are curious to see whether retailing businesses, one of the most robust industries in US, have been affected, and if affected, how have the industry been affected. In order to gain the required insight, we first acquire stock prices of six representative retailing companies in US, then we apply ARIMA model on the data to forecast their trends in the near future, which will imply the general robustness of the industry. This procedure includes testing the stationary of time series data of stocks, and finding the suitable ARIMA parameters for each stock, using various methods. Accuracy metrics are brought into discussion to determine how accurate our forecast is. Finally, we draw the conclusion that ARIMA model, being a suitable method for our case of study, has given us desirable result: the stocks of 6 selected retailing companies will perform steadily with slight increase at the end of the year. There are several practical values or our research: By applying ARIMA models on stocks of retailing companies, we discovered that application of such models on retailing industry is not only pragmatic, but effective; and the results of our analysis provide future researchers with insight of economy of this era of pandemic.

Citation Download Citation

Yi Lu, Zihan Wang, and Yihan Wang "The application of ARIMA model in retailing industry and forecasting on economic trend of industry", Proc. SPIE 12330, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022), 1233019 (23 August 2022); https://doi.org/10.1117/12.2646621

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KEYWORDS

Data modeling

Autoregressive models

Analytical research

Error analysis

Time series analysis

Inspection

Lutetium

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