Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/42439
Title: Neural network with genetically evolved algorithms for stocks prediction
Authors: Phua, P.K.H. 
Ming, D. 
Lin, W. 
Keywords: Artificial neural network
Genetic algorithm
Nonlinear time series
Stock market prediction
Issue Date: 2001
Source: Phua, P.K.H.,Ming, D.,Lin, W. (2001). Neural network with genetically evolved algorithms for stocks prediction. Asia-Pacific Journal of Operational Research 18 (1) : 103-107. ScholarBank@NUS Repository.
Abstract: Many studies have shown that artificial neural networks have the capability to learn the underlying mechanics of stock markets. In fact, artificial neural networks have been widely used for forecasting financial markets. However, such applications to Singapore stock markets are scarce. This paper applies genetically evolved neural network models to predict the Straits Times Index (STI) of the Stock Exchange of Singapore (SES). Our studies show that satisfactory results can be achieved when applying genetically evolved neural networks to predict the STI.
Source Title: Asia-Pacific Journal of Operational Research
URI: http://scholarbank.nus.edu.sg/handle/10635/42439
ISSN: 02175959
Appears in Collections:Staff Publications

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