| Issue |
ITM Web Conf.
Volume 56, 2023
First International Conference on Data Science and Advanced Computing (ICDSAC 2023)
|
|
|---|---|---|
| Article Number | 05009 | |
| Number of page(s) | 8 | |
| Section | Machine Learning & Neural Networks | |
| DOI | https://doi.org/10.1051/itmconf/20235605009 | |
| Published online | 09 August 2023 | |
Comparative Analysis of Machine Learning Algorithms to Forecast Indian Stock Market
Department of Information Technology, VNR Vignana Jyothi Institute Of Engineering and Technology, Hyderabad, Telangana, India
* Correspondingauthor: gnchandrika@gmail.com
Forecasting the stock market is a complex and challenging task, as it involves analyzing a vast amount of data and taking into account various economic, political, and social factors. This paper presents an overview of different approaches and techniques used for stock market forecasting, including fundamental analysis and machine learning. The study also highlights the different algorithms used and discusses their effectiveness in predicting the stock market. This research proposes to use five different algorithms as Decision Trees, Random forest, Generalized Linear model,Gradient boosted trees, and Support Vector Machines. This research identifies models that are close to real predictions. These algorithms are applied to BSE index data from November 2017 to February28, 2023.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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