Using a weightless neural network to forecast stock prices: A case study of Nigerian stock exchange

Please use this identifier to cite or link to this item: http://ir.futminna.edu.ng:8080/jspui/handle/123456789/1773

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DC Field	Value	Language
dc.contributor.author	Alhassan, J. K.	-
dc.contributor.author	Misra, Sanjay	-
dc.date.accessioned	2021-06-06T18:23:31Z	-
dc.date.available	2021-06-06T18:23:31Z	-
dc.date.issued	2011	-
dc.identifier.citation	, https://doi.org/10.5897/SRE10.1040	en_US
dc.identifier.issn	3DC0E6925286	-
dc.identifier.uri	http://repository.futminna.edu.ng:8080/jspui/handle/123456789/1773	-
dc.description.abstract	This research work, proposes forecasting stock prices in the stock market industry in Nigeria using a Weightless Neural Network (WNN). A neural network application used to demonstrate the application of the WNN in the forecasting of stock prices in the market is designed and implemented in Visual Foxpro 6.0. The proposed network is tested with stock data obtained from the Nigeria Stock Exchange. This system is compared with Single Exponential Smoothing (SES) model. The WNN error value is found to be 0.39 while that of SES is 9.78, based on these values, forecasting with the WNN is observed to be more accurate and closer to the real data than those using the SES model.	en_US
dc.publisher	Academic Journals - Scientific Research and Essay	en_US
dc.relation.ispartofseries	Volume 6 Number 14;	-
dc.subject	Weightless Neural Network, Single Exponetial Smoothing	en_US
dc.title	Using a weightless neural network to forecast stock prices: A case study of Nigerian stock exchange	en_US
dc.type	Article	en_US
Appears in Collections:	Computer Science

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