Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Forecasting Stock Market Movement Direction Using Sentiment Analysis and Support Vector Machine
Stockholms universitet, Samhällsvetenskapliga fakulteten, Företagsekonomiska institutionen. University of Chinese Academy of Science, China.
Rekke forfattare: 32019 (engelsk)Inngår i: IEEE Systems Journal, ISSN 1932-8184, E-ISSN 1937-9234, Vol. 13, nr 1, s. 760-770Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Investor sentiment plays an important role on the stock market. User-generated textual content on the Internet provides a precious source to reflect investor psychology and predicts stock prices as a complement to stock market data. This paper integrates sentiment analysis into a machine learning method based on support vector machine. Furthermore, we take the day-of-week effect into consideration and construct more reliable and realistic sentiment indexes. Empirical results illustrate that the accuracy of forecasting the movement direction of the SSE 50 Index can be as high as 89.93% with a rise of 18.6% after introducing sentiment variables. And, meanwhile, our model helps investors make wiser decisions. These findings also imply that sentiment probably contains precious information about the asset fundamental values and can be regarded as one of the leading indicators of the stock market.

sted, utgiver, år, opplag, sider
2019. Vol. 13, nr 1, s. 760-770
Emneord [en]
Day-of-week effect, decision making, sentiment analysis, stock markets, text mining
HSV kategori
Identifikatorer
URN: urn:nbn:se:su:diva-167646DOI: 10.1109/JSYST.2018.2794462ISI: 000459697700072OAI: oai:DiVA.org:su-167646DiVA, id: diva2:1303036
Tilgjengelig fra: 2019-04-08 Laget: 2019-04-08 Sist oppdatert: 2019-04-08bibliografisk kontrollert

Open Access i DiVA

Fulltekst mangler i DiVA

Andre lenker

Forlagets fulltekst

Søk i DiVA

Av forfatter/redaktør
Wu, Desheng Dash
Av organisasjonen
I samme tidsskrift
IEEE Systems Journal

Søk utenfor DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric

doi
urn-nbn
Totalt: 48 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf