An Epsilon Constraint Method for selecting Indicators for use in Neural Networks for Stock Market Forecasting

References

• Abu-Mostafa Y, Atiya A (1996): Introduction to Financial Forecasting. Applied Intelligence, 6:205–213
   Web of Science ®Google Scholar
• Buliali J.L, Fatichah C, Susanto M (2009) Hybrid Neural Network-Monte Carlo Simulation for stock price index prediction; Asian Journal of Information Technology; 8; 1; 1–7.
   Google Scholar
• Chang P, Fan C, Liu C (2009): Integrating a Piecewise Linear Representation Method and a Neural Network Model for Stock Trading Points Prediction. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews; 39; 1; 80–92.
   Web of Science ®Google Scholar
• Chankong V. and Haimes Y.Y. (1983): Multiobjective Decision Making Theory and Methodology. Elsevier Science, New York.
   Google Scholar
• Cheng C, Chen T, Wei L (2010): A hybrid model based on rough sets theory and genetic algorithms for stock price forecasting; Information Sciences; 160; 9; 1610–1629.
   Google Scholar
• Chenowwth T, Obradovic Z, Lee S (1996): Embedding Technical Analysis into Neural Network Based Trading Systems; Applied Artificial Intelligence, an international journal; 10; 6; 523–542.
   Google Scholar
• Coupelon O (2011) Neural Network Modeling for Stock Movement Prediction: A State of the Art (1st ed.) [Online]. Available: http://olivier.coupelon.free.fr/Neural_network_modeling_for_stock_movement_prediction.pdf
   Google Scholar
• Ehrgott M, Wiecek M.M. (2005): Multiobjective Programming," in “Multiple Criteria Decision Analysis: State of the Art Survey; J. Figueira, S. Greco & M. Ehrgott, Eds. Springer; 667–722.
   Google Scholar
• Fernandez-Blanco P, Bodas-Sagi D, Soltero F, Hidalgo J (2008): Technical Market Indicators Optimization using Evolutionary Algorithms, Proceedings of the 10th annual conference companion on Genetic and evolutionary computation; 1851–1858
   Google Scholar
• Garza-Gomez X, Metghalchi M, Chen C (2010): Technical Analysis: Evidence from the Mexican Stock Market. University of Houston-Victoria, The Business Review; Cambridge; 15.
   Google Scholar
• Gorgulho A, Neves R, Horta N (2011): Applying a GA kernel on optimizing technical analysis rules for stock picking and portfolio composition. Expert Systems with Applications; 38; 14072–14085.
   Web of Science ®Google Scholar
• Guresen E., Kayakutlu G., Daim T.U. (2011): Using artificial neural network models in stock market index prediction; Expert Systems with Applications; 38; 10389–10397
   Web of Science ®Google Scholar
• Kim K (2006): Artificial Neural Networks with Evolutionary Instance Selection for Financial Forecasting. Expert Systems with Applications; 30; 519–526.
   Web of Science ®Google Scholar
• Kim K (2004): Artificial Neural Networks with Feature Transformation Based on Domain Knowledge for the Prediction of Stock Index Futures, Intelligent Systems in Accounting, Finance and Management; 12; 167–176
   Google Scholar
• Kim M, Min S.H, Han I (2006): An Evolutionary Approach to the Combination of Multiple Classifiers to Predict a Stock Price Index; Expert Systems with Applications 31; 241–247.
   Web of Science ®Google Scholar
• Kuo R.J, Chen C.H, Hwang Y.C (2001): An Intelligent Stock Trading Decision Support System through integration of genetic algorithm based fuzzy neural network and artificial neural network; Fuzzy Sets and Systems; 118; 1; 21–45.
   Web of Science ®Google Scholar
• Lakshminarayanan S (2005): An Integrated Stock Market Forecasting Model Using Neural Networks; MSc. Thesis, College of Engineering and Technology of Ohio University, Ohio, United States of America.
   Google Scholar
• Majhi R, Panda G, Sahoo G (2009): Development and performance evaluation of FLANN based model for forecasting of stock markets. Expert Systems with Applications; 36; 6800–6808.
   Google Scholar
• Padhiary P.K, Mishra A.P (2011): Development of Improved Artificial Neural Network Model for Stock Market Prediction; International Journal of Engineering Science and Technology; 3; 2; 1576–1580.
   Google Scholar
• Steuer, R. E. (1986). Multiple Criteria Optimization: Theory, Computation and Application, Wiley Series in Probability and Mathematical Statistics, John Wiley
   Google Scholar
• Wei L, Chen T, Ho T (2011): A Hybrid Model Based on Adaptive-Network –Based Fuzzy Inference System to Forecast Taiwan Stock Market. Expert Systems and Applications; 38; 13625–13631
   Web of Science ®Google Scholar
• Yao J, Tan C, Poh H (1999): Neural Networks for Technical Analysis: A Study on KLCI; International Journal of Theoretical and Applied Finance; 2; 221–241.
   Google Scholar