Assessing model efficacy in forecasting EPS of Chinese firms using fundamental accounting variables: a comparative study
by Qing Cao, Qiwei Gan, Marc J. Schniederjans
International Journal of Society Systems Science (IJSSS), Vol. 2, No. 3, 2010

Abstract: In this paper, we compare the forecasting accuracy of two neural network models in forecasting earnings per share of Chinese listed companies based upon fundamental accounting variables. In one neural network model, weights estimated by back propagation were utilised, and in the other model a genetic algorithm was utilised. Based upon a sample of 723 Chinese companies in 22 industries over a ten year period, we found that the neural network model, using a genetic algorithm in forecasting, outperforms the neural network model with back propagation. Results also showed that the addition of fundamental accounting variables used in the neural network models further improved forecasting accuracy.

Online publication date: Wed, 02-Jun-2010

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