The Prediction of Stock Market Using Recurrent Neural Network

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dc.contributor.advisorMohammad Monirujjaman Khan
dc.contributor.authorSadman Bin Islam
dc.contributor.authorMohammad Mahabubul Hasan
dc.contributor.id1611957042
dc.contributor.id1421274042
dc.coverage.departmentElectrical and Computer Engineering
dc.date.accessioned2025-07-30
dc.date.accessioned2025-07-30T10:06:26Z
dc.date.available2025-07-30T10:06:26Z
dc.date.issued2021
dc.description.abstractStock price forecasting is becoming increasingly popular recently in the financial realm. Shares price prediction is important for increasing the interest of speculators in putting money in a company's stock in order to grow the number of shareholders in the stock. Successfully predicting the future price of a stock could result in a sizable return. When it involves forecasting, various methodologies are used. This report uses a replacement stock price prediction framework is proposed utilizing a well-liked model which is Recurrent Neural Network (RNN) model i.e., Long Short-Term Memory (LSTM) model. It is often shown from the simulation results that utilizing these RNN models, i.e., LSTM, and with proper hyper-parameter tuning, the proposed scheme can forecast future stock trend with high accuracy. The RMSE for LSTM model was measured by varying the number of epochs, difference between predicted stock price and actual stock price. The model is trained and evaluated for accuracy with various sizes of knowledge. The assessments are conducted by utilizing a freely accessible dataset for stock markets having date, volume, open, high, low, and closing prices. The major goal of this article is to determine to what degree a Machine Learning algorithm can anticipate the stock market price with greater accuracy.
dc.description.degreeUndergraduate
dc.identifier.cd600000621
dc.identifier.print-thesisTo be assigned
dc.identifier.urihttps://repository.northsouth.edu/handle/123456789/1340
dc.language.isoen
dc.publisherNorth South University
dc.rights© NSU Library
dc.titleThe Prediction of Stock Market Using Recurrent Neural Network
dc.typeThesis
oaire.citation.endPage54
oaire.citation.startPage1
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