GCMT-189 An Efficient Time Series Analysis for Pharmaceutical Sector Stock Prediction by Applying Hybridization of Data Mining and Neural Network Technique

GCMT-189 An Efficient Time Series Analysis for Pharmaceutical Sector Stock Prediction by Applying Hybridization of Data Mining and Neural Network Technique

The nonlinearity of the stock market is widely accepted all over the world and to reveal such non-linearity the most effective technique has proved to be constructed through application of either data mining or neural network. Pharmaceutical sector is a rapidly growing sector in Bangladeshi stock...

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Bibliographic Details
Main Authors: Das, Debashish, Sadiq, Ali Safa, Noraziah, Ahmad
Format: Conference or Workshop Item
Language:English
Published: 2015
Online Access:http://umpir.ump.edu.my/id/eprint/20938/
http://umpir.ump.edu.my/id/eprint/20938/1/GCMT-189%20An%20Efficient%20Time%20Series%20Analysis%20for%20Pharmaceutical%20Sector%20Stock%20Prediction%20by%20Applying%20Hybridization.pdf

Internet

http://umpir.ump.edu.my/id/eprint/20938/
http://umpir.ump.edu.my/id/eprint/20938/1/GCMT-189%20An%20Efficient%20Time%20Series%20Analysis%20for%20Pharmaceutical%20Sector%20Stock%20Prediction%20by%20Applying%20Hybridization.pdf

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