Stock index modeling using EDA based local linear wavelet neural network

Proceedings of 2005 International Conference on Neural Networks and Brain Proceedings, ICNNB'05

Volumn 3, Issue , 2005, Pages 1646-1650

  Chen, Yuehui ^a   Dong, Xiaohui ^a   Zhao, Yaou ^a  

^a UNIVERSITY OF JINAN   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; FINANCIAL DATA PROCESSING; MATHEMATICAL MODELS; OPTIMIZATION; WAVELET TRANSFORMS;

ESTIMATION OF DISTRIBUTION ALGORITHM (EDA); LOCAL LINEAR WAVELET NEURAL NETWORK (LLWNN); STOCK INDEX; STOCK MARKET;

NEURAL NETWORKS;

EID: 33847140556     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (19)

1. Abraham A., Nath B. and Mahanti P.K., "Hybrid Intelligent Systems for Stock Market Analysis", Computational Science, Springer-Verlag Germany, Vassil N Alexandrov et al (Editors), USA, (2001)337-345.
2. Abraham A., Philip N.S., and Saratchandran P., "Modeling Chaotic Behavior of Stock Indices Using Intelligent Paradigms", International Journal of Neural, Parallel and Scientific Computations, USA, Volume 11, Issue (1,2), (2003)143-160.
3. Leigh W., Modani N., Purvis R. and Roberts T., "Stock market trading rule discovery using technical charting heuristics", Expert Systems with Applications 23(2), (2002)155-159.
4. Leigh W., Purvis R. and Ragusa J.M., "Forecasting the NYSE composite index with technical analysis, pattern recognizer, neural network, and genetic algorithm: a case study in romantic decision support", Decision Support Systems 32(4),(2002)361-377.
5. Nasdaq Stock MarketSM, http://www.nasdaq.com
6. National Stock Exchange of India Limited, http://www.nse-india.com
7. Chen Y. and A. Abraham, "Hybrid Learning Methods for Stock Index Modeling", Book chapter, Artificial Neural Networks in Finance,Health and Manufacturing: Potential and Challenges, J. Kamruzzaman, R. K. Begg and R. A. Sarker (Eds.), Idea Group Inc. Publishers, USA, 2005. (In Press)
8. Chen, Y., Yang, B., Dong, J., "Time-Series Prediction using a Local Linear Wavelet Neural Network", Neurocomputing, 2005 (In press).
9. Chen, Y., Yang, B., Dong, J., Abraham A., "Time-series forecasting using flexible neural tree model", Information Science, Vol.174, Issues 3/4, pp.219-235, 2005.
10. Moore A. and Schneider J. and Deng K., "Efficient Locally Weighted Polynomial Regression Predictions", Proceedings of the Fourteenth International Conference on Machine Learning, (1997)236-244.
11. Bosman, P. A. N. and Thierens, D. (2000), "Expanding from Discrete to Continuous EDAs: The IEDA", Proceedings of Parallel Problem Solving from Nature, PPSN-VI, pp. 767-776
12. Muehlenbein, H. and Paa; G. (1996), "From Recombination of Genes to the Estimation of Distribution", Part 1, Binary Parameter, Lecture Notes in Computer Science 1141, Parallel Problem Solving from Nature, pp. 178-187.
13. Rudlof, S. and Koppen M., "Stochastic Hill-Climbing with Learning by Vectors of Normal Distributions", Nagoya, Japan, 1996.
14. Larraenaga, P. and Lozano, J. A. (2001), "Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation", Kluwer Academic Publishers.
15. S. Tsuteui, M. Pelikan, and D. E. Goldberg, "Evolutionary Algorithm Using Marginal Histogram Models in Continuous Domain", In Proceedings of the 2001 Genetic and Evolutionary Computation Conference Workshop, 230-233, 2001.
16. Pelikan, M. and Goldberg, D. E. and Cantu-Paz, E. (1999), "BOA: The Bayesian optimization algorithm", In Proceedings of the Genetic and Evolutionary Computation Conference GECCO-99, W. Banzhaf and J. Daida and A. E. Eiben and M. H. Garzon and V. Honavar and M. Jakiela and R. E. Smith (Eds), Morgan Kaufmann Publishers, San Francisco, CA,Orlando, FL, vol. 1, pp. 525-532.
17. Zhang, B. T. (1999), "A Bayesian Framework for Evolutionary Computation", Proceedings of the 1999 Congress on Evolutionary Computation, vol.1, pp. 722-228.
18. rd Int. Industrial Fuzzy Control and Intelligent Systems, 134-139, 1993.
19. Fischer, B., O. Nelles and R. Isermann, "Adaptive predictive control of a heat exchanger based on a fuzzy model", Control Engineering Practice, 6: 259-269, 1998.