Forecasting EPS of Chinese Listed Companies Using Neural Network with Genetic Algorithm

In this paper we use neural network models to forecast earnings per share (EPS) of Chinese listed companies using fundamental accounting variables. The sample includes 723 Chinese companies in 22 industries over 10 years. The result shows that the neural network model with weights estimated with genetic algorithm (GA) outperforms the neural network with weights estimated with back propagation (BP). Results also show that the addition of fundamental accounting variables used in the neural network models further improves the forecasting accuracy.

[1]  Roger J. Calantone,et al.  Artificial Neural Network Decision Support Systems for New Product Development Project Selection , 2000 .

[2]  Brian J. Bushee,et al.  Abnormal Returns to a Fundamental Analysis Strategy , 1997 .

[3]  Gregory R. Madey,et al.  The Application of Neural Networks and a Qualitative Response Model to the Auditor's Going Concern Uncertainty Decision* , 1995 .

[4]  Filippo Menczer,et al.  Customer Targeting: A Neural Network Approach Guided by Genetic Algorithms , 2005, Manag. Sci..

[5]  Dongwei Su.  Stock price reactions to earnings announcements: evidence from Chinese markets , 2003 .

[6]  Robin L. Tarpley,et al.  Contextual Fundamental Analysis Through the Prediction of Extreme Returns , 2001 .

[7]  Xiaoning Zhang,et al.  Data Mining for Network Intrusion Detection: A Comparison of Alternative Methods , 2001, Decis. Sci..

[8]  David J. Groggel,et al.  Practical Nonparametric Statistics , 2000, Technometrics.

[9]  B. Lev,et al.  Fundamental Information Analysis , 1993 .

[10]  Yufei Yuan,et al.  Neural network forecasting of quarterly accounting earnings , 1996 .

[11]  S. Hyakin,et al.  Neural Networks: A Comprehensive Foundation , 1994 .

[12]  Randall S. Sexton,et al.  Simultaneous optimization of neural network function and architecture algorithm , 2004, Decis. Support Syst..

[13]  Li-Wei Chen,et al.  Integration of the grey relational analysis with genetic algorithm for software effort estimation , 2008, Eur. J. Oper. Res..

[14]  Y.-S. Lin,et al.  A hybrid knowledge discovery model using decision tree and neural network for selecting dispatching rules of a semiconductor final testing factory , 2005 .

[15]  P. Cheng,et al.  Corporate Governance and the Harmonisation of Chinese Accounting Practices with IFRS Practices , 2007 .

[16]  Manuel Landajo,et al.  Robust neural modeling for the cross-sectional analysis of accounting information , 2007, Eur. J. Oper. Res..

[17]  Dennis Murray,et al.  Note on Adjustments to Analysts' Earnings Forecasts Based Upon Systematic Cross-Sectional Components of Prior-Period Errors , 1995 .

[18]  Ruey-Shun Chen,et al.  Design of a product quality control system based on the use of data mining techniques , 2006 .

[19]  Wei Zhang,et al.  Neural Network Earnings per Share Forecasting Models: A Comparative Analysis of Alternative Methods , 2004, Decis. Sci..

[20]  Tsvi Kuflik,et al.  Filtering search results using an optimal set of terms identified by an artificial neural network , 2006, Inf. Process. Manag..

[21]  Brian J. Bushee,et al.  Fundamental Analysis Future Earnings, and Stock Prices , 1997 .

[22]  Hon-Kwong Lui,et al.  Machine Learning for Direct Marketing Response Models: Bayesian Networks with Evolutionary Programming , 2006, Manag. Sci..

[23]  Jeffrey E. Jarrett,et al.  Forecasting Seasonal Time Series of Corporate Earnings: A Note* , 1990 .

[24]  Marc J. Schniederjans,et al.  A comparison between Fama and French's model and artificial neural networks in predicting the Chinese stock market , 2005, Comput. Oper. Res..

[25]  Kuldeep Kumar,et al.  Artificial neural network vs linear discriminant analysis in credit ratings forecast: A comparative study of prediction performances , 2006 .

[26]  Lawrence D. Brown,et al.  Univariate Time-Series Models of Quarterly Accounting Earnings per Share: A Proposed Model , 1979 .

[27]  Randall S. Sexton,et al.  Optimization of neural networks: A comparative analysis of the genetic algorithm and simulated annealing , 1999, Eur. J. Oper. Res..

[28]  Kevin C. W. Chen,et al.  Earnings Management and Capital Resource Allocation: Evidence from China's Accounting‐Based Regulation of Rights Issues , 2004 .

[29]  Robert E. Dorsey,et al.  Genetic algorithms for estimation problems with multiple optima , 1995 .

[30]  Nallan C. Suresh,et al.  Performance of Selected Part‐Machine Grouping Techniques for Data Sets of Wide Ranging Sizes and Imperfection , 1994 .

[31]  Min Qi,et al.  Nonlinear Predictability of Stock Returns Using Financial and Economic Variables , 1999 .