Please use this identifier to cite or link to this item: https://elibrary.khec.edu.np:8080/handle/123456789/442
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dc.contributor.advisorEr. Prakash Chandra Prasad-
dc.contributor.advisorEr. Anand Kumar Sah-
dc.contributor.authorRajthala, Bibash KCE074BCT014-
dc.contributor.authorRokaya, Sangat KCE074BCT039-
dc.contributor.authorTimilsina, Subin KCE074BCT042-
dc.contributor.authorAcharya, Sujan KCE074BCT043-
dc.date.accessioned2022-12-04T10:03:43Z-
dc.date.available2022-12-04T10:03:43Z-
dc.date.issued2021-
dc.identifier.urihttps://elibrary.khec.edu.np/handle/123456789/442-
dc.description.abstractStock market prediction is a thriving topic across the globe, millions of new dematerialised accounts were opened in past few years. In the context of Nepal, Demat account holder has reached to the count of 48,95,021 as of 16th Feb 2022. Craze in investment over company’s stocks has seen an exponential growth. Stock market prediction has been a challenging problem for both economists and data scientists. For the sake of building effective prediction model, various researchers are coming with new techniques and approaches achieving good yet capricious results as market depends upon various stochastic factors. Hence, stock prediction methods incorporating the technical and sentiment analysis has been best for assisting investors in general. With the dataset available sentiment analysis was performed with 71.75% accuracy and with GRU accuracy of 70.11% to predict the future price of stock. Adversarial training accuracy was 53.25% for the trend prediction.en_US
dc.language.isoenen_US
dc.subjectAdversarial Learning, LSTM, Neural Network, XL-Net, Transformer XL,en_US
dc.titleSTOCK MARKET PREDICTION USING SENTIMENT AND TECHNICAL ANALYSISen_US
dc.typeTechnical Reporten_US
local.college.nameKhwopa College of Engineering-
local.degree.departmentDepartment of Computer-
local.degree.nameB.E. Computer-
local.degree.levelBacherlor's Degree-
local.item.accessionnumberTUD.239-
Appears in Collections:Computer Report

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