Authors :
Ujwal C; Varun U K; Vishwas Gowda U; Manoj K Y; Kala Chandrashekar
Volume/Issue :
Volume 6 - 2021, Issue 7 - July
Google Scholar :
http://bitly.ws/9nMw
Scribd :
https://bit.ly/2WFbpw8
Abstract :
This paper here presents how different
algorithms can be implemented to find the stock price.
Algorithms such as Linear Regression, KNN, Random
Forest Regression, Elastic Net and LSTM model are
implemented. The main aim of this paper is to find the
trend of the stock i.e predict whether the price of the
stock is going to increase or decrease the next day. The
average of the predicted values are taken and the value is
predicted. Since predicting the future value of the stock is
highly dependent on various factors such as current
trend, social media engagements, public involvement etc.
Hence the best way to get the exact value of the stock is
by predicting one day into the future.
Keywords :
Stock Prediction, Machine Learning (ML), Regression
This paper here presents how different
algorithms can be implemented to find the stock price.
Algorithms such as Linear Regression, KNN, Random
Forest Regression, Elastic Net and LSTM model are
implemented. The main aim of this paper is to find the
trend of the stock i.e predict whether the price of the
stock is going to increase or decrease the next day. The
average of the predicted values are taken and the value is
predicted. Since predicting the future value of the stock is
highly dependent on various factors such as current
trend, social media engagements, public involvement etc.
Hence the best way to get the exact value of the stock is
by predicting one day into the future.
Keywords :
Stock Prediction, Machine Learning (ML), Regression
