Paper Title :Using Financial and Economic Leading Indicators to Predict Sales of Publicly Traded Companies
Author :Hong Long Chen
Article Citation :Hong Long Chen ,
(2019 ) " Using Financial and Economic Leading Indicators to Predict Sales of Publicly Traded Companies " ,
International Journal of Management and Applied Science (IJMAS) ,
pp. 58-63,
Volume-5,Issue-6
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.
Type : Research paper
Published : Volume-5,Issue-6
DOIONLINE NO - IJMAS-IRAJ-DOIONLINE-15717
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Copyright: © Institute of Research and Journals
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Published on 2019-08-19 |
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