Publish In |
International Journal of Management and Applied Science (IJMAS)-IJMAS |
Journal Home Volume Issue |
||||||||
Issue |
Volume-5,Issue-6 ( Jun, 2019 ) | |||||||||
Paper Title |
Using Financial and Economic Leading Indicators to Predict Sales of Publicly Traded Companies | |||||||||
Author Name |
Hong Long Chen | |||||||||
Affilition |
Department of Business and Management, The National University of Tainan | |||||||||
Pages |
58-63 | |||||||||
Abstract |
This article proposes a modeling procedure that combines time series and regression analysis for estimating sales of publicly traded companies based on internal financial and economic leading indicators. First, this article proposes a data transformation equation to improve linear relationships between preceding financial and economic variables and sales performance. Second, based on these improved relationships, a modeling procedure that combines time series and regression analysis is used to develop sales forecasting models for four sample construction companies. The out-of-sample forecasting accuracy is evaluated using mean absolute percentage error (MAPE). The results show that the MAPE values in the forecasting models range from 0.89% to 4.94% with an average of 2.68%, which outperforms a similar study that uses the vector auto regression (VAR) model and the Litter man Bayesian vector auto regression (LBVAR) model. Keywords - Sales Forecasting, Structural Model, Time Series Regression Model. | |||||||||
View Paper |