An empirical analysis about forecasting Tmall air-conditioning sales using time series model

Abstract Time series model is a hotspot in the research of statistics. On November 11, 2015, Tmall platform’s turnover was more than $91.2 billion which caused the attention of scholars both at home and abroad. So this paper aims to forecast sales of Tmall, which is helpful to the enterprises. Research methods are ARIMA model and VAR model. The first model is single-variable model and the later is multi-variable model. In the study, ARIMA model makes the sequence smooth by using two difference operation. In VAR model, five explanatory variables are transformed into one main component. By contrast, VAR model does not give detailed accurate prediction, but ARIMA model does. Therefore, single-variable time series model is more suitable for sales forecast than multi-variable model.

Keywords ARIMA model, VAR model, Sales forecast.

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Dynamic analyses of a flat plate and a beam subjected to a moving load

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