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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM21682
Volume:
7 |
6 |
Jun 2023
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
It is very difficult to predict stock prices because there are no clear forecast rules in the stock market, but it gives the highest returns in the market. Although volatile in nature, stock prices and other statistical factors can be visualized to help interested investors make prudent decisions about which companies to spend their profits on. Developing this simple project idea in Python allows you to create dynamic graphs of financial data for a given company using tabular data provided by the Python library yfinance. In addition, future stock prices can be predicted using the LTSM machine learning algorithm. This project is a great introduction for Python/data science newbies and a good refresher for experts who have already worked with Python/ML.
KEYWORDS
Publication Date
6/27/2023
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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