DOIONLINE

DOIONLINE NO - IJMAS-IRAJ-DOIONLINE-15717

Publish In
International Journal of Management and Applied Science (IJMAS)-IJMAS
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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.
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