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Implementation of time series approaches to financial data

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bracu.degree.levelUndergraduate
bracu.type.groupStudent Works
datacite.rightsOpen Access
dc.contributor.advisorMajumdar, Dr. Mahbub
dc.contributor.authorSadat, Noshin Nawar
dc.contributor.departmentDepartment of Computer Science and Engineering
dc.date.accessioned2016-09-08T05:48:51Z
dc.date.available2016-09-08T05:48:51Z
dc.date.copyright2016
dc.date.issued2016-08
dc.descriptionCataloged from PDF version of thesis report.
dc.descriptionIncludes bibliographical references (page 82-83).
dc.descriptionThis thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016.en_US
dc.description.abstractWe study a time series approach to nancial data, speci cally the ARIMA models, and build a web based platform for stock market enthusiasts to analyze time series of stock market returns data and to t ARIMA models to the series to forecast future returns. This system also acts as an informative tool by providing helpful instructions to the users regarding the analysis and model- tting procedure. It uses R to perform the statistical computations.en_US
dc.description.degreeBachelor of Science in Computer Science and Engineering
dc.description.statementofresponsibilityNoshin Nawar Sadat
dc.format.extent83 pages
dc.identifier.otherID 12101017
dc.identifier.urihttp://hdl.handle.net/10361/6393
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.rightsBRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectTime series approachesen_US
dc.subjectAutocorrelation functionen_US
dc.titleImplementation of time series approaches to financial dataen_US
dc.typeThesisen_US

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