Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/99520
Title: Forecasting the KLSE index using neural networks
Authors: Yao, Jingtao 
Poh, Hean-Lee 
Issue Date: 1995
Citation: Yao, Jingtao,Poh, Hean-Lee (1995). Forecasting the KLSE index using neural networks. IEEE International Conference on Neural Networks - Conference Proceedings 2 : 1013-1017. ScholarBank@NUS Repository.
Abstract: Neural networks have been actively researched by computer scientists and engineers for many years. They have captured the attention of business community in recent years and potential applications of the technology have emerged, such as the application of neural networks in forecasting. In this paper, based on the rescaled range analysis, the indices of Kuala Lumpur Stock Exchange (KLSE) are predicted by the popularly used backpropagation neural network. The choice of KLSE is an interesting one, as KLSE is one of the largest stock markets in the emerging economies in terms of capitalization. Using different trading strategies, a significant paper profit can be achieved by purchasing indexed stocks in the respective proportions. The experiment shows that useful predictions can be made without the use of extensive market data or knowledge.
Source Title: IEEE International Conference on Neural Networks - Conference Proceedings
URI: http://scholarbank.nus.edu.sg/handle/10635/99520
Appears in Collections:Staff Publications

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