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Published in:   Vol. 4 Issue 1 Date of Publication:   June 2015

Prediction of Stock using Artificial Neural Networks (A Survey)

G.Sundar,K.Satyanarayana

Page(s):   22- 25 ISSN:   2278-2397
DOI:   10.20894/IJBI.105.004.001.006 Publisher:   Integrated Intelligent Research (IIR)


  1. S. Madria, S. Bhowmick,   "Stock Price Prediction Using Artificial Neural Network",   International Journal of Innovative Research in Sc   ,Vol.3   ,Issue 6   ,1999
    View Artical

  2. Mayankkumar B Patel,Sunil R Yalamalle,   "Optimumneur Network Architecture For Stock Market Forecasting   ,2014
    View Artical

  3. Gitansh khirbat ,Rahul gupta,Sanjay singh,   "Predicting the BSE Sensex:Performance comparison of adaptive linear element, feed forward and time d   ,2013
    View Artical

  4. Binu Nair, Patturajan, M. ; Mohandas, V,   "Application ofArtificial Neural Network for stock marketpredictions: A review of literature",   International Journal of Machine Intelligence   ,Vol.2   ,Issue 2   ,2012
    View Artical

  5. Dase R.K. and Pawar D.D,   "Economic prediction usingneural networks: the case of IBM daily stockreturns",   Department of Economics Universityof California, S   ,Vol.2   ,Issue 2   ,2010
    View Artical

  6. Halbert White,   "Guidelines for Financial Prediction with Artificial neural networks
    View Artical

  7. JingTao YAO and Chew Lim TAN,   "A Neural networkbased fuzzy time seriesmodel to improve forecasting   ,Vol.37   ,Issue 4
    View Artical

  8. Tiffany Hui-Kuang yu and Kun-Huang Huarng,   "Translated Nigeriastock market price using artificial neuralnetwork for effective prediction",   Journal oftheoretical and Applied Informationtechn   ,2010
    View Artical

  9. Akinwale Adio T, Arogundade O.T andAdekoya Adebayo F,   "Theuse of data mining and neural networks forforecasting stock market returns   ,Vol.29   ,Issue 4   ,2009
    View Artical

  10. David Enke and Suraphan Thawornwong,   "Price Prediction of Share Market using Artificial Neural Network (ANN)",   International Journal of Computer Applications   ,Vol.22   ,Issue 2   ,2005
    View Artical

  11. Z.H. Khan, T.S. Alin and M.A. Hussain,   "Discovering stock price prediction rules using rough sets",   Neural network world   ,2011
    View Artical

  12. H. Al-Qaheri, A. E. Haassanien, and A. Abraham,,   "An empirical methodology for developing stock market trading systems using artificial neural network",   An international journal of expert systems with ap   ,Vol.36   ,Issue 3   ,2008
    View Artical

  13. Bruce Vanstone & Gavin Finnie,   "Optimal combination of trading rules using neural networks",   International business   ,Vol.2   ,Issue 1   ,2009
    View Artical

  14. Mitra Subrata Kumar,   "Stock market forecasting: Artificial neural networks and linear regression comparison in an emerging",   Journal of financial management and analysis   ,Vol.18   ,Issue 2   ,2009
    View Artical

  15. Altay, E., and Satman, M.H.,   "Stock price direction prediction using artificial neural network approach: The case of Turkey",   Journal of artificial Intelligence   ,Vol.1   ,Issue 2   ,2005
    View Artical

  16. Senol, D., and Ozturan, M.,   "A comparison of global, recurrent and smoothed-piecewise neural models for Istanbul stock exchange p",   Pattern recognition letters   ,Vol.26   ,Issue 13   ,2008
    View Artical

  17. Yumulu, S. Gurgen, F, Okay N,   "financial forecasting with artificial neural networks",   Ankara University, Institute of social sciences, M   ,Vol.14   ,Issue 1   ,2004
    View Artical

  18. Vural B.B,   "Financial predicting with artificial neural networks in crisis periods: The case of ISE 100 index",   International symposium on International Capital F   ,2007
    View Artical

  19. Akel, V., and Bayramoglu, M.F,   "Predicting the Brazilian stock market through neural networks and adaptive exponential smoothing met",   Expert system Applications.   ,Vol.36   ,Issue 10   ,2008
    View Artical

  20. E.L. de Faria and J.L. Gonzalez,   "Evaluating the Employment of Technical Indicators in Predicting Stock Price Index Variations Using A",   International Journal of Business and Management   ,Vol.7   ,Issue 15   ,2009
    View Artical