Stock price prediction during pandemic situation

bracu.type.groupResearch Publications
datacite.rightsMetadata Only
dc.contributor.authorDas, Kaushik
dc.contributor.authorAhmed, Nazia
dc.contributor.authorTabasshum, Anika
dc.contributor.authorAzad, Tahzib
dc.contributor.authorChowdhury, Nuzhat
dc.contributor.authorMostakim, Moin
dc.contributor.authorNoor, Jannatun
dc.contributor.departmentDepartment of Computer Science and Engineering
dc.date.accessioned2026-09-23T06:44:01Z
dc.date.available2026-09-23T06:44:01Z
dc.date.issued2023-01-01
dc.description.abstractAccurately predicting the stock value enables investors to earn more money, reducing their uncertainty on whether to buy or sell. Again during the COVID-19 period, many companies have shown a different picture of the stock market situation. That is why investors cannot consider the company's exact status in the stock market. The primary objective of our paper is to predict the future behavior of the stock market in the event of a pandemic using machine learning classification. To consider the future stock market condition, first, we looked at the past stock market condition and tried to make predictions by collecting data from two companies. Second, we tried to understand what happened in the stock market during the pandemic and used machine learning algorithms. Finally, make predictions through machine learning classifications by merging the data during the pandemic with past data. In conclusion, we have attempted to identify what was lacking in our instance and provide a concise description of the next steps.
dc.description.versionPublished
dc.format.extent6 Pages
dc.identifier.citationK. Das et al., "Stock Price Prediction During Pandemic Situation," 2023 26th International Conference on Computer and Information Technology (ICCIT), Cox's Bazar, Bangladesh, 2023, pp. 1-6, doi: 10.1109/ICCIT60459.2023.10441168.
dc.identifier.doi10.1109/ICCIT60459.2023.10441168
dc.identifier.issn9798350359015
dc.identifier.other2-s2.0-85187369900
dc.identifier.urihttps://hdl.handle.net/10361/30177
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.hasversion10.1109/ICCIT60459.2023.10441168
dc.relation.ispartof2023 26th International Conference on Computer and Information Technology Iccit 2023
dc.relation.ispartofseries2023 26th International Conference on Computer and Information Technology Iccit 2023
dc.relation.urihttps://ieeexplore.ieee.org/document/10441168
dc.subjectCOVID-19
dc.subjectUncertainty
dc.subjectPandemics
dc.subjectBiological system modeling
dc.subjectPredictive models
dc.subjectData models
dc.subjectStock markets
dc.subjectPrediction
dc.subject.lcshStock price forecasting.
dc.titleStock price prediction during pandemic situation
dc.typeConference Proceeding
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.identifier.scopus-author-id58930285900
person.identifier.scopus-author-id58930872200
person.identifier.scopus-author-id58931449300
person.identifier.scopus-author-id58930286000
person.identifier.scopus-author-id58930872300
person.identifier.scopus-author-id55758417600
person.identifier.scopus-author-id57193917145

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
IMG_8345.jpg
Size:
27.35 KB
Format:
Joint Photographic Experts Group/JPEG File Interchange Format (JFIF)

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: