Using Arima Model to Forecast Sales of an Automobile Company
Author(s):
Nirbhay Pherwani , Vivekanand Education Society's Institute of Technology; Vyjayanthi Kamath, Vivekanand Education Society's Institute of Technology
Keywords:
ARIMA, Sales Forecast, Data Analysis, Time Series, Automobile Sales Forecast
Abstract:
When it comes to running businesses successfully, sales forecasting is a crucial component to include in the process. In this paper, the aim is to forecast the sales made by an automobile company in a particular city. The data outlines the total sales of the company manufactured cars at the end of the month from 2013 to 2014. Utilizing this data, we fit the Autoregressive Integrated Moving Average (ARIMA) time series with the regression model. Utilizing the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) values, we identify the best fit ARIMA model and use this to obtain the sales forecast for the subsequent year. To successfully build the model we use R Programming.
Other Details:
| Manuscript Id | : | IJSTEV4I5024
|
| Published in | : | Volume : 4, Issue : 5
|
| Publication Date | : | 01/12/2017
|
| Page(s) | : | 77-82
|
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