Please use this identifier to cite or link to this item: http://hdl.handle.net/11718/10087
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dc.contributor.authorDutta, Goutam
dc.contributor.authorJha, Pankaj
dc.contributor.authorLaha, Arnab Kumar
dc.contributor.authorMohan, Neeraj
dc.date.accessioned2010-10-29T06:42:57Z
dc.date.available2010-10-29T06:42:57Z
dc.date.copyright2006
dc.date.issued2006-10-29T06:42:57Z
dc.identifier.urihttp://hdl.handle.net/11718/10087
dc.descriptionJournal of Emerging Market Finance, Vol. 5, No. 3, (October - December, 2006), pp. 283 - 95en
dc.description.abstractANN has been shown to be an efficient tool for non-parametric modeling of data in a variety of different contests where the output is a non-linear function of the inputs. These include business forecasting, credit scoring, bond rating, business failure prediction, medicine, pattern recognition, and image processing. A large number of studies have been reported in the literature with reference to use of ANN in modeling stock prices in the Western countries. However, not much work along these lines has been reported in the Indian context.
dc.language.isoenen
dc.subjectArtificial Neural Networken
dc.subjectBombay Stock Exchangeen
dc.subjectStock Priceen
dc.titleArtificial neural network models for forecasting stock price index in the Bombay stock exchangeen
dc.typeArticleen
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