Authors :
Dr. Chaitanya Kishore Reddy.M; K.Pradeep; V.Luke Sundar; A.Devi Priya
Volume/Issue :
Volume 8 - 2023, Issue 4 - April
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://bit.ly/3HXuTRH
Abstract :
Long-term research has focused heavily on
the prediction of stock values. Predicting stock prices has
been one of the biggest concerns in recent years. Trading
stocks is a significant economic activity that contributes
to society and enables individuals to increase their
income. Making a prediction about the stock market
involves attempting to anticipate the future value of a
company's stock or another financial instrument traded
on a stock exchange. Gains for investors will be
maximized if a stock's future price can be accurately
predicted. The stock market's issue is that it occasionally
displays an erratic pattern that could result in a crash.
Stock price predictions frequently involve machine
learning techniques. We employ a variety of machine
learning techniques, both supervised and unsupervised,
to inform investors of stock price increases and
decreases. Data acquisition, dataset preprocessing,
feature extraction, feature-based stock price prediction,
and result presentation were the five stages of the
process. Data is initially gathered from various social
media platforms and historical company information.
Pre-processing is the second phase, where incorrect,
duplicate, and dirt data are removed. In the third phase,
data sets are reduced and meaningful data are chosen. In
the fourth phase, predictions are made utilizing various
machine learning methods, including supervised and
unsupervised learning techniques. Now, various methods
are used in the final phase to determine correctness.
Keywords :
Tesla, Elon Musk, Stock Market, Linear Regression, Machine Learning
Long-term research has focused heavily on
the prediction of stock values. Predicting stock prices has
been one of the biggest concerns in recent years. Trading
stocks is a significant economic activity that contributes
to society and enables individuals to increase their
income. Making a prediction about the stock market
involves attempting to anticipate the future value of a
company's stock or another financial instrument traded
on a stock exchange. Gains for investors will be
maximized if a stock's future price can be accurately
predicted. The stock market's issue is that it occasionally
displays an erratic pattern that could result in a crash.
Stock price predictions frequently involve machine
learning techniques. We employ a variety of machine
learning techniques, both supervised and unsupervised,
to inform investors of stock price increases and
decreases. Data acquisition, dataset preprocessing,
feature extraction, feature-based stock price prediction,
and result presentation were the five stages of the
process. Data is initially gathered from various social
media platforms and historical company information.
Pre-processing is the second phase, where incorrect,
duplicate, and dirt data are removed. In the third phase,
data sets are reduced and meaningful data are chosen. In
the fourth phase, predictions are made utilizing various
machine learning methods, including supervised and
unsupervised learning techniques. Now, various methods
are used in the final phase to determine correctness.
Keywords :
Tesla, Elon Musk, Stock Market, Linear Regression, Machine Learning
