Stockwise: A survey on stock price prediction models
Abstract
Stock prices are difficult to predict because they can
change a lot and are affected by various factors. People,
especially investors, care a lot about predicting them accurately.
By properly predicting stock prices, it is very useful to those
investors who invest in the stock market to get profit. There are
plenty of machine learning and deep learning models available
for prediction. Some of the models predict very accurately, and
others do not. So, the selection of a prediction model is an
important factor for predicting the stock price. This paper
mainly focuses on comparing different prediction models based
on performance measure.
Keywords:
Stock price, Prediction models, Machine learningPublished
Issue
Section
License
Copyright (c) 2024 International Journal on Emerging Research Areas

This work is licensed under a Creative Commons Attribution 4.0 International License.
All published work in this journal is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
How to Cite
Similar Articles
- Alan K George, Arpita Mary Mathew, Asin Mary Jacob, Elizabeth Antony, Shiney Thomas, Lung Cancer Subtype Classification Using Deep Learning Models , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Raihana Rasaldeen, Stefi Marshal Fernandez, Irin Rose Jaison, Ria Mariam , A Comparative Study of AI Models and AI-Based Approaches for Evaluating Subjective Answers in Exams , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Muneebah Mohyiddeen, Sana T.H, Anoodh Hussain, Nandana P Narayanan, Sneha Soman, DGCURE: Model for Detection of Dysgraphia , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Fabeela Ali Rawther, Akhil P Dominic, Alan James, Christy Chacko, Elena Maria Varghese, Early Detection of Attention Deficiency Using ML , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- George P Kurias, Gokul Krishna AU, Jifith Joseph, Sharunmon R, Linsa Mathew, A Review of Methodologies for Detecting Missing and Wanted People Using Machine Learning and Video Surveillance , International Journal on Emerging Research Areas: Vol. 4 No. 2 (2024): IJERA
- Adona Shibu, Aarunya Retheep, Albin Joseph, Ali Jasim, Adona Shibu , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Adithya Satheesh, Ashwin S Nair, Darren Padamittam Jacob, Athul Rajeev, Er. Maheshwary Sreenath, Intrusion Countermeasure System , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Mishal Rose Thankachan, Joshua John Sajit, Merwin Maria Antony, Richa Maria Biju, Richa Maria Biju, Bini M Issac, Pixelyse : ViT- VAE for Document Forgery Detection , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Albin Thomas Lalu, Resmara S, Alen A Thankachen, Sneha Priya Sebastian, Dany Jennez , Lirin Blesson, Kesia Sunny, Fault Detection of Transmission Lines Using Unmanned Aerial Vehicle (UAV) , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Adithya Satheesh, Ashwin S Nair, Darren Padamittam Jacob, Athul Rajeev, Er. Maheshwary Sreenath, Intrusion Countermeasure System , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
You may also start an advanced similarity search for this article.
