Please use this identifier to cite or link to this item:
Title: Sectorial stock market prediction using neural networks : a Singapore case.
Authors: Lee, Melvin Pei Chang.
Keywords: DRNTU::Business::Finance::Equity
Issue Date: 2000
Abstract: This research attempts to ascertain the usefulness of neural networks in predicting stock prices in the Singapore stock market. Specifically, experiments are set to test how well neural networks can perform price prediction on different sectors of the market. It is hypothesized that forecasting sectorial indices should yield better predictability than forecasting the cover-all "Allshare" index. If this hypothesis is supported, neural training for stock market prediction should thus be sectorial-focused.
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:NBS Theses

Files in This Item:
File Description SizeFormat 
  Restricted Access
11.58 MBAdobe PDFView/Open

Page view(s) 50

checked on Sep 28, 2020

Download(s) 50

checked on Sep 28, 2020

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.