Machine Learning Approaches in Stock Price Prediction

Author(s)	Dargupalli Shravani, Patlola Shashi Rekha, Yelakala Aparna, Narla Keerthi, G.Surekha
Country	India
Abstract	The stock market is becoming more widespread. One of the convoluted things to do in the stock market is to do a prediction or analysis of the stock price. Market volatility and sovereign factors are impacting stock values. As a result, any stock market expert will have difficulty predicting the growth or collapse of a particular stock. So, here we are studying various algorithms for the prediction purpose, comparing all those algorithms via RSME metrics, and using the best one for the prediction.
Keywords	Open Value, High Value, Low Value, Last Value, Close Value, Total Trade Quantity, Turnover (Lacs), RMSE, LSTM.
Field	Engineering
Published In	Volume 5, Issue 2, March-April 2023
Published On	2023-04-21
Cite This	Machine Learning Approaches in Stock Price Prediction - Dargupalli Shravani, Patlola Shashi Rekha, Yelakala Aparna, Narla Keerthi, G.Surekha - IJFMR Volume 5, Issue 2, March-April 2023. DOI 10.36948/ijfmr.2023.v05i02.2482
DOI	https://doi.org/10.36948/ijfmr.2023.v05i02.2482
Short DOI	https://doi.org/gr6h9k

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