Please use this identifier to cite or link to this item:
https://ptsldigital.ukm.my/jspui/handle/123456789/578540| Title: | External constraints of neural cognition for cimb stock closing price prediction |
| Authors: | Chang Sim Vui (UMS) Chin Kim On (UMS) Gan Kim Soon (UMS) Rayner Alfred (UMS) Patricia Anthony |
| Keywords: | Artificial Neural Network (ANNS) Backpropagation Feedforward Neural Network (FFNN) Levenberg-Marquardt algorithm Macroeconomic parameters Stock market forecasting |
| Issue Date: | Jun-2017 |
| Description: | This paper investigates the accuracy of Feedforward Neural Network (FFNN) with different external parameters in predicting the closing price of a particular stock. Specifically, the feedforward neural network was trained using Levenberg-Marquardt backpropagation algorithm to forecast the CIMB stock’s closing price in the Kuala Lumpur Stock exchange (KLSE). The results indicate that the use of external parameters can improve the accuracy of the stock’s closing price. |
| News Source: | Pertanika Journals |
| ISSN: | 0128-7680 |
| Volume: | 25 |
| Pages: | 29-38 |
| Publisher: | Universiti Putra Malaysia Press |
| Appears in Collections: | Journal Content Pages/ Kandungan Halaman Jurnal |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| ukmvital_116006+Source01+Source010.PDF | 824.37 kB | Adobe PDF |  View/Open |
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