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

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