dc.contributor.author | Dutta, Goutam | |
dc.contributor.author | Jha, Pankaj | |
dc.contributor.author | Laha, Arnab Kumar | |
dc.contributor.author | Mohan, Neeraj | |
dc.date.accessioned | 2010-10-29T06:42:57Z | |
dc.date.available | 2010-10-29T06:42:57Z | |
dc.date.copyright | 2006 | |
dc.date.issued | 2006-10-29T06:42:57Z | |
dc.identifier.uri | http://hdl.handle.net/11718/10087 | |
dc.description | Journal of Emerging Market Finance, Vol. 5, No. 3, (October - December, 2006), pp. 283 - 95 | en |
dc.description.abstract | ANN 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.iso | en | en |
dc.subject | Artificial Neural Network | en |
dc.subject | Bombay Stock Exchange | en |
dc.subject | Stock Price | en |
dc.title | Artificial neural network models for forecasting stock price index in the Bombay stock exchange | en |
dc.type | Article | en |