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http://drsr.daiict.ac.in//handle/123456789/952
Title: | Machine learning in financial data EPS estimates |
Authors: | Joshi, M.V. Sharma, Rohan |
Keywords: | Machine Learning Earning per Share |
Issue Date: | 2020 |
Citation: | Sharma, Rohan (2020). Machine learning in financial data EPS estimates. Dhirubhai Ambani Institute of Information and Communication Technology. iv, 13 p. (Acc.No: T00874) |
Abstract: | The 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. |
URI: | http://drsr.daiict.ac.in//handle/123456789/952 |
Appears in Collections: | M Tech Dissertations |
Files in This Item:
File | Description | Size | Format | |
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201811046.pdf Restricted Access | 615.27 kB | Adobe PDF | View/Open Request a copy |
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