Predicting Stock Closing Price Using Machine Learning Techniques

Authors

  • Akash Asthana Department of Statistics, University of Lucknow, Lucknow 226007, Uttar Pradesh, India
  • Syed Shafi Ahmed Department of Statistics, University of Lucknow, Lucknow 226007, Uttar Pradesh, India https://orcid.org/0000-0002-5047-5050
  • Yash Srivastava Department of Statistics, University of Lucknow, Lucknow 226007, Uttar Pradesh, India

DOI:

https://doi.org/10.26713/jfbms.v3i1.2538

Keywords:

Machine learning, neural network, Random forest, Support Vector machine, Long-Short term memory

Abstract

Predicting the stock price have been very challenging and profitable task. Since the introduction of artificial intelligence and machine learning techniques, the efficiency of prediction improved to a great extent. An attempt has been made in the present study to predict the closing price of the selected stocks using machine learning and deep neural network techniques. The data of top companies of the Indian stock market for the period from April 2016 to March 2021 have been used. It was obtained that the deep learning model, i.e., LSTM gave better results than the other machine learning model.

Downloads

Download data is not yet available.

Downloads

Published

2024-08-30
CITATION

How to Cite

Asthana, A., Ahmed, S. S., & Srivastava, Y. (2024). Predicting Stock Closing Price Using Machine Learning Techniques. Journal of Finance, Business and Management Studies, 3(1), 11–17. https://doi.org/10.26713/jfbms.v3i1.2538

Issue

Vol. 3 No. 1 (2023)

Section

Articles