Deep Learning Applied to Public Company Valuation for Value Investing

dc.contributor.authorHaich, Abram Paul
dc.date.accessioned2022-06-02T19:09:52Z
dc.date.available2022-06-02T19:09:52Z
dc.date.issued2021
dc.description.abstractValue investing is an investing approach that seeks to discover and take advantage of price discrepancies between the market price and the actual value of a company (intrinsic value). The purpose of this work is to measure the intrinsic value of companies using an approach that has had success in the broad field of Artificial Intelligence, Deep Learning. Finding patterns in large amounts of data is what Deep Learning can be used for. Typically for value investing an investor will seek to find conservative estimates on the current value of a company by analyzing fundamental data. Our method attempts to perform these estimates in a data driven manor using Deep Learning to estimate the intrinsic value of a company with the overall goal of aiding the Investor in uncovering undervalued companies.en_US
dc.identifier.urihttps://hdl.handle.net/10365/32668
dc.publisherNorth Dakota State Universityen_US
dc.rightsNDSU policy 190.6.2en_US
dc.rights.urihttps://www.ndsu.edu/fileadmin/policy/190.pdfen_US
dc.subjectdeep learningen_US
dc.subjectdiscount cash flowen_US
dc.subjectvalue investingen_US
dc.titleDeep Learning Applied to Public Company Valuation for Value Investingen_US
dc.typeThesisen_US
ndsu.advisorLi, Juan
ndsu.collegeEngineeringen_US
ndsu.degreeMaster of Science (MS)en_US
ndsu.departmentComputer Scienceen_US

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