Show simple item record

Social Media Analysis of 'Meme Stocks'

dc.contributor.authorAnason, Nicholas
dc.contributor.authorDaines, Alexander
dc.contributor.advisorRomero, Daniel
dc.date.accessioned2023-05-26T17:56:17Z
dc.date.available2023-05-26T17:56:17Z
dc.date.issued2022
dc.identifier.urihttps://hdl.handle.net/2027.42/176743
dc.description.abstractIn January 2021, stocks such as GME and AMC saw a rapid increase in value coinciding with their rise in popularity among online communities of smaller “retail” investors. It was therefore speculated heavily in the media that these communities’ interest directly caused the increases in these stocks, dubbed ‘Meme Stocks’ due to their disproportionate popularity in online communities. This project examines the relationship between online social media sites, specifically r/wallstreetbets, and the performance of the stocks popular there. We attempt to establish empirically what stocks are more popular based on trends in vocabulary. Then, we examined the relationship between activity on r/wallstreetbets and the adjusted closing prices and implied volatility of the popular stocks. Finally, we attempt to create a model to predict the price and implied volatility of certain stocks based on activity on r/wallstreetbets.
dc.subjectSocial Media
dc.subjectNatural Language Processing
dc.subjectMarkets
dc.subjectOptions
dc.titleSocial Media Analysis of 'Meme Stocks'
dc.typeProject
dc.subject.hlbtoplevelEngineering
dc.description.peerreviewedNA
dc.contributor.affiliationumData Science
dc.contributor.affiliationumCognitive Science
dc.contributor.affiliationumcampusAnn Arbor
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/176743/1/Social_Media_Analysis_of_Meme_Stocks_-_Nicholas_Anason.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/176743/2/Social_Media_Analysis_of_Meme_Stocks_Poster_-_Nicholas_Anason.pdf
dc.identifier.doihttps://dx.doi.org/10.7302/7592
dc.working.doi10.7302/7592en
dc.owningcollnameHonors Program, The College of Engineering


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.