Social Sentiment and Stock Trading Via Mobile Phones

dc.contributor.author Kim K.
dc.contributor.author Lee S.-Y.T.
dc.contributor.author Kauffman R.J.
dc.date.accessioned 2023-06-16T15:06:30Z
dc.date.available 2023-06-16T15:06:30Z
dc.date.issued 2016
dc.description Auburn University;Claremont Graduate University;et al.;Kennesaw State University;SAP;University Of Tennessee Chattanooga en_US
dc.description 22nd Americas Conference on Information Systems: Surfing the IT Innovation Wave, AMCIS 2016 -- 11 August 2016 through 14 August 2016 -- 123256 en_US
dc.description.abstract What happens when uninformed investors trade stocks via mobile phones? Do they react to social sentiment differently than more informed traders in traditional trading? Based on 16,817 data observations and econometric analysis for the trading of 251 equities in Korea over 39 days, we present evidence of herding behavior among uninformed traders in the mobile channel. The results indicate that mobile traders seem more easily swayed by changing social sentiment. In addition, stock trading in the traditional channel probably influences sentiment formation in the market overall. Mobile traders follow signals in social media suggesting that they engage in less beneficial herding behavior, based on evidence that we obtained for the occurrence of more negative feedback trading. This allows us to offer a new interpretation of how mobile channel stock trading works, and open a new portal for analytics with digital data related to the trading behavior of different investors. en_US
dc.identifier.scopus 2-s2.0-84987619315
dc.identifier.uri https://hdl.handle.net/20.500.14365/3962
dc.language.iso en en_US
dc.publisher Association for Information Systems en_US
dc.relation.ispartof AMCIS 2016: Surfing the IT Innovation Wave - 22nd Americas Conference on Information Systems en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Econometric analysis en_US
dc.subject Herding behavior en_US
dc.subject Investor reactions en_US
dc.subject Machine learning en_US
dc.subject Mobile channel en_US
dc.subject Social media en_US
dc.subject Social sentiment en_US
dc.subject Stock trading en_US
dc.subject Uninformed traders en_US
dc.subject Value traders en_US
dc.subject Artificial intelligence en_US
dc.subject Cellular telephones en_US
dc.subject E-learning en_US
dc.subject Financial markets en_US
dc.subject Information systems en_US
dc.subject Learning systems en_US
dc.subject Mobile devices en_US
dc.subject Mobile phones en_US
dc.subject Social networking (online) en_US
dc.subject Telephone sets en_US
dc.subject Econometric analysis en_US
dc.subject Herding behaviors en_US
dc.subject Investor reactions en_US
dc.subject Mobile channels en_US
dc.subject Social media en_US
dc.subject Social sentiment en_US
dc.subject Stock trading en_US
dc.subject Uninformed traders en_US
dc.subject Value traders en_US
dc.subject Commerce en_US
dc.title Social Sentiment and Stock Trading Via Mobile Phones en_US
dc.type Conference Object en_US
dspace.entity.type Publication
gdc.author.scopusid 54902688100
gdc.author.scopusid 35083571300
gdc.coar.access metadata only access
gdc.coar.type text::conference output
gdc.description.departmenttemp Kim, K., Izmir University of Economics, Turkey; Lee, S.-Y.T., Hanyang University, South Korea; Kauffman, R.J., Singapore Management University, Singapore en_US
gdc.description.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality N/A
gdc.description.wosquality N/A
gdc.identifier.wos WOS:000559951902105
gdc.index.type WoS
gdc.index.type Scopus
gdc.scopus.citedcount 7
gdc.wos.citedcount 0
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relation.isOrgUnitOfPublication.latestForDiscovery e9e77e3e-bc94-40a7-9b24-b807b2cd0319

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