Article ID: | iaor2009426 |
Country: | United States |
Volume: | 35 |
Issue: | 2 |
Start Page Number: | 205 |
End Page Number: | 237 |
Publication Date: | Apr 2005 |
Journal: | Decision Sciences |
Authors: | Schniederjans Marc J., Cao Qing, Zhang Wei |
Keywords: | decision theory, forecasting: applications |
In this paper, we present a comparative analysis of the forecasting accuracy of univariate and multivariate linear models that incorporate fundamental accounting variables (i.e., inventory, accounts receivable, and so on) with the forecast accuracy of neural network models. Unique to this study is the focus of our comparison on the multivariate models to examine whether the neural network models incorporating the fundamental accounting variables can generate more accurate forecasts of future earnings than the models assuming a linear combination of these same variables.