A NEURAL NETWORK APPROACH TO FORECASTING EARNINGS PER SHARE

Authors

W. Raghupathi, Department of Accounting and Management Information Systems, California State UniversityFollow

Abstract

This paper explores the potential of neural networks to forecast earnings per share. The neural network would serve as a decision support system for finance managers, stock brokers and investment analysts and investors. Results of experiments with training/testing indicate that neural networks appear to be promising in forecasting EPS. Further investigations are necessary.

Recommended Citation

Raghupathi, W., "A NEURAL NETWORK APPROACH TO FORECASTING EARNINGS PER SHARE" (1996). AMCIS 1996 Proceedings. 37.
https://aisel.aisnet.org/amcis1996/37