A neural network-based ensemble forecasting method for financial market prediction

International Journal of Advanced Mechatronic Systems

Volumn 3, Issue 4, 2011, Pages 259-267

  Xu, Wei ^a   Zuo, Meiyun ^a   Zhang, Mingtao ^a   He, Rong ^a  

^a RENMIN UNIVERSITY OF CHINA   (China)

Author keywords

Ensemble method; Financial market; Neural network; Prediction; Stock price

Indexed keywords

EID: 84862752102     PISSN: 17568412     EISSN: 17568420     Source Type: Journal    
DOI: 10.1504/IJAMECHS.2011.043374     Document Type: Conference Paper

References (40)

1. An, A.M., Hao, X.H., Su, H.Y. and Wang, Q. (2010)'Non-linear model predictive control based on neural network model with modified differential evolution adapting weights', International Journal of Advanced Mechatronic Systems, Vol. 2, No. 3, pp.182-191.
2. Atsalakis, G.S. and Valavanis, K.P. (2009)'Surveying stock market forecasting techniques - part II: soft computing methods', Expert Systems with Applications, Vol. 36, No. 3, pp.5932-5941.
3. Benediktsson, J.A., Sveinsson, J.R., Ersoy, O.K. and Swain, P.H. (1997)'Parallel consensual neural networks', IEEE Trans. Neural Networks, January, Vol. 8, No. 1, pp.54-64. (Pubitemid 127767780)
4. Bermak, A. and Martinez, D. (2003)'A compact 3-D VLSI classifier using bagging threshold network ensembles', IEEE Transactions on Neural Networks, September, Vol. 14, No. 5, pp.1097-1109.
5. Box, G.E.P. and Jenkins, G. (1970) Time Series Analysis: Forecasting and Control, Holden-Day, San Francisco, CA.
6. Breiman, L. (1994)'Bias, variance, and arcing classifiers', Tech. Rep. No. 460, Department of Statistics, University of California.
7. Breiman, L. (1996a)'Bagging predictors', Machine Learning, Vol. 24, No. 2, pp.123-140. (Pubitemid 126724382)
8. Breiman, L. (1996b)'Stacked regressions', Machine Learning, Vol. 24, No. 1, pp.49-64. (Pubitemid 126724379)
9. Cao, Q., Leggio, K.B. and Schniederjans, M.J. (2005)'A comparison of Fama, French's model and artificial neural network in predicting the Chinese stock market', Computers & Operations Research, Vol. 32, No. 10, pp.2499-2512. (Pubitemid 40219757)
10. Freund, Y. and Schapire, R.E. (1999)'A short introduction to boosting', Journal of Japanese Society for Artificial Intelligence, September, Vol. 14, No. 5, pp.771-780.
11. Fumera, G., Roli, F. and Serrau, A. (2008)'A theoretical analysis of bagging as a linear combination of classifiers', IEEE Transactions on Pattern Analysis and Machine Intelligence, July, Vol. 30, No. 7, pp.1293-1299.
12. Harrald, P.G. and Kamstra, M. (1997)'Evolving artificial neural networks to combine financial forecasts', IEEE Trans. Evolutionary Computation, April, Vol. 1, No. 1, pp.40-52. (Pubitemid 127771017)
13. Hassan, M.R., Nath, B. and Kirley, M. (2007)'A fusion model of HMM, ANN and GA for stock market forecasting', Expert Systems with Applications, Vol. 33, No. 10, pp.171-180. (Pubitemid 44959927)
14. Ho, T.K. (1998)'The random subspace method for constructing decision forests', IEEE Transactions on Pattern Analysis and Machine Intelligence, August, Vol. 20, No. 8, pp.832-844. (Pubitemid 128741345)
15. Hsu, S.H., Hsieh, J.J.P.A., Chih, T.C. and Hus, K.C. (2009)'A two-stage architecture for stock price forecasting by integrating self-organizing map and support vector regression', Expert Systems with Applications, Vol. 36, No. 4, pp.7947-7951.
16. Hsu, C., Hsu, C., Lee, T. and Lin, C. (2010)'FPGA-based position tracking controller design with fuzzy wavelet neural networks', International Journal of Advanced Mechatronic Systems, Vol. 2, Nos. 5/6, pp.297-305.
17. Huang, C.L., Chen, M.C. and Wang, C.J. (2007)'Credit scoring with a data mining approach based on support vector machines', Expert Systems with Applications, Vol. 33, No. 4, pp.847-856.
18. Hung, J.C. (2009)'A fuzzy GARCH model applied to stock market scenario using a genetic algorithm', Expert Systems with Applications, Vol. 36, No. 9, pp.11710-11717.
19. Ince, H. and Trafalis, T.B. (2007)'Kernel principal component analysis and support vector machines for stock price prediction', IIE Transactions, Vol. 39, No. 6, pp.629-637. (Pubitemid 46502165)
20. Kanas, A. and Yannopoulos, A. (2001)'Comparing linear and nonlinear forecasts for stock returns', International Review of Economics and Finance, Vol. 10, No. 4, pp.383-398. (Pubitemid 33666959)
21. Kim, K.J. and Han, I. (2000)'Genetic algorithms approach to feature discretization in artificial neural networks for the prediction of stock price index', Expert Systems with Applications, Vol. 19, No. 2, pp.125-132.
22. Kim, M.J., Min, S.H. and Han, I. (2006)'An evolutionary approach to the combination of multiple classifiers to predict a stock price index', Expert Systems with Applications, Vol. 31, No. 2, pp.241-247. (Pubitemid 44294438)
23. Kohzadi, N., Boyd, M.S., Kermanshahi, B. and Kaastra, I. (1996)'A comparison of artificial neural network and time series model for forecasting commodity prices', Neurocomputing, Vol. 10, No. 2, pp.169-181. (Pubitemid 26082147)
24. Krogh, A. and Vedelsby, J. (1995)'Neural network ensembles, cross validation, and active learning', Tesauro, G., Touretzky, D. and Leen D. (Eds.): Advances in Neural Information Processing Systems, pp.231-238, The MIT Press, Massachusetts.
25. Lai, K.K., Wang, S. and Yu, L. (2008)'Forecasting foreign exchange rates using an SVR-based neural network ensemble', Ravi, V. (Ed.): Advances in Banking Technology and Management: Impacts of ICT and CRM, pp.261-277, IGI Global, London.
26. Lee, R.S.T. (2004)'IJADE stock advisor: an intelligent agent based stock prediction system using hybrid RBF recurrent network', IEEE Trans. System, Man, and Cybernetics - Part A, Systems and Humans, May, Vol. 34, No. 3, pp.421-428.
27. Liao, Z. and Wang, J. (2010)'Forecasting model of global stock index by stochastic time effective neural network', Expert Systems with Applications, Vol. 37, No. 1, pp.834-841.
28. Lu, C., Devos, A., Suykens, J.A.K., Arus, C. and Huffel, S.V. (2007)'Bagging linear sparse Baynesian learning models for variable selection in cancer diagnosis', IEEE Transactions on Information Technology in Biomedicine, May, Vol. 11, No. 3, pp.338-347. (Pubitemid 46746184)
29. Murat, Y.S. and Ceylan, H. (2006)'Use of artificial neural network for transport energy demand modeling', Energy Policy, Vol. 34, No. 17, pp.3165-3172. (Pubitemid 44204045)
30. Pai, P.F. and Lin, C.S. (2005)'A hybrid ARIMA and support vector machines model in stock price forecasting', Omega, Vol. 33, No. 6, pp.497-505.
31. Perrone, M.P. and Cooper, L.N. (1993)'When networks disagree: ensemble methods for hybrid neural networks', Mammone, R.J. (Ed.): Neural Networks for Speech and Image Processing, pp.126-142, Chapman-Hall.
32. Refenes, A.P.N. and Holt, W.P. (2001)'Forecasting volatility with neural regression: a contribution to model adequacy', IEEE Trans. Neural Networks, July, Vol. 12, No. 4, pp.850-864.
33. Roh, T.H. (2007)'Forecasting the volatility of stock price index', Expert Systems with Applications, Vol. 33, No. 4, pp.916-922.
34. Tao, D., Tang, X., Li, X. and Wu, X. (2006)'Asymmetric bagging and random subspace for support vector machines-based relevance feedback in image retrieval', IEEE Trans. on Pattern Analysis and Machine Intelligence, July, Vol. 28, No. 7, pp.1088-1099.
35. Thomakos, D.D. and Jr, J.B.G. (2004)'Naïve, ARIMA, nonparametric, transfer function, and VAR models: a comparison of forecasting performance', International Journal of Forecasting, Vol. 20, No. 1, pp.53-67. (Pubitemid 38148294)
36. Tseng, F.M., Yu, H.C. and Tzeng, G.H. (2002)'Combining neural network model with seasonal time series ARIMA model', Technological Forecasting & Social Change, Vol. 69, No. 1, pp.71-87.
37. Valenzuela, O., Rojas, I., Rojas, F., Pomares, H., Herrera, L.J., Guillen, A., Marquez, L. and Pasadas, M. (2008)'Hybridization of intelligent techniques and ARIMA models for time series prediction', Fuzzy Sets and Systems, Vol. 159, No. 7, pp.821-845.
38. Wu, W., Feng, G., Li, Z. and Xu, Y. (2005)'Deterministic convergence of an online gradient method for BP neural network', IEEE Trans. Neural Network, May, Vol. 16, No. 3, pp.533-540. (Pubitemid 40718001)
39. Yu, L., Chen, H., Wang, S. and Lai, K.K. (2009)'Evolving least squares support vector machines for stock market trend mining', IEEE Trans. Evolutionary Computation, February, Vol. 13, No. 1, pp.87-102.
40. Zhang, G.P., Patuwo, B.E. and Hu, M.Y. (1998)'Forecasting with artificial neural networks: the state of the art', International Journal of Forecasting, Vol. 14, No. 1, pp.35-62.