Abstract
In today's world, Artificial Intelligence and Deep Learning are getting popular regularly. The various applications areas of artificial intelligence are related to human activity. One of the general application areas of neural networks and artificial intelligence is prediction analysis. In this paper, the authors also have performed one comparative study based on artificial intelligence. Authors have performed stock market predictions using different models. In reality, stock markets are entirely volatile, so there is very much a requirement of good prediction analysis for judging the stocks prices and their ups and downs with time. The stock prices can easily be predicted using machine learning algorithms on data available in financial news, as this data can also change investors' interests. However, traditional prediction methods have become obsolete and do not provide accurate predictions over non-stationary time series data. This paper proposes a stock price prediction method that gives accurate results with the advancements in deep learning technologies.
Recommended Citation
Jaiswal, Rupashi; Mahato, Kunal; Kapoor, Pankaj; and Pal, Dr. Sudipta Basu
(2024)
"A Comparative Analysis on Stock Price Prediction Model using DEEP LEARNING Technology,"
American Journal of Electronics & Communication (AJEC): Vol. 2:
Iss.
3, Article 3.
Available at:
https://research.smartsociety.org/ajec/vol2/iss3/3