A Comparative Study Of Backpropagation Algorithms In Financial Prediction

Salim Lahmiri
2011 International Journal of Computer Science Engineering and Applications  
Stock market price index prediction is a challenging task for investors and scholars. Artificial neural networks have been widely employed to predict financial stock market levels thanks to their ability to model nonlinear functions. The accuracy of backpropagation neural networks trained with different heuristic and numerical algorithms is measured for comparison purpose. It is found that numerical algorithm outperform heuristic techniques.
doi:10.5121/ijcsea.2011.1402 fatcat:x7igqvnmffb3xmsqdwmno4daum