Stock price prediction

Abstract

Accurately predicting the stock value enables investors to earn more money, reducing their uncertainty on whether to buy and 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.

Description

Cataloged from PDF version of thesis.
Includes bibliographical references (pages 43-45).
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.

Keywords

Stock market, Prediction, Data mining, Covid-19

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