Please use this identifier to cite or link to this item: http://drsr.daiict.ac.in//handle/123456789/952
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dc.contributor.advisorJoshi, M.V.
dc.contributor.authorSharma, Rohan
dc.date.accessioned2020-09-22T20:12:33Z
dc.date.available2023-02-16T20:12:33Z
dc.date.issued2020
dc.identifier.citationSharma, Rohan (2020). Machine learning in financial data EPS estimates. Dhirubhai Ambani Institute of Information and Communication Technology. iv, 13 p. (Acc.No: T00874)
dc.identifier.urihttp://drsr.daiict.ac.in//handle/123456789/952
dc.description.abstractThe project “EPS Estimates” is as the name suggests a work on Earnings Per Share figures released by companies annually and quarterly. The whole project is intended to come up with a better consensus methodology for EPS Estimates given by different brokers and give the clients a better idea of what the EPS figures will be like. There are various statistical methods and machine learning models used for the purpose and a comparison is done between them in this report. The details about the intuition behind the models, their shortcomings and some insights behind them are included in this report.
dc.subjectMachine Learning
dc.subjectEarning per Share
dc.classification.ddc006.31 SHA
dc.titleMachine learning in financial data EPS estimates
dc.typeDissertation
dc.degreeM. Tech
dc.student.id201811046
dc.accession.numberT00874
Appears in Collections:M Tech Dissertations

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