Prediction in Stock Market Value using Artificial Intelligence
Currently, investments made via the purchase of stock shares account for the majority of international trades among countries and significant quantities of cash are traded on stock markets around the globe. However, one of the most important things is to figure out how to efficiently condense & visualize stock market data in a way that people or organizations may use it to make well-informed investing decisions. In order to identify patterns in chaotic and nonlinear systems, this paper proposes a smart stock market forecasting system that uses fuzzy inference and neural networks. This study aims to predict the price of stocks using the financial data of a company.By utilizing a probe to look at a sample of the entire population. The prediction was made by a nonlinear fuzzy-neural network framework with the stock market acting as an external variable.
Authors
- Akash Akash (ORCID: https://orcid.org/0000-0002-6155-1821)
- Daya Bhardwaj
- S. Bhatia (ORCID: https://orcid.org/0009-0007-5533-9123)
- Lakshay Bhardwaj
Institutions
- Manav Rachna International Institute of Research and Studies (IN)
Publication Details
- Published
- 2024-12-13
- DOI
- https://doi.org/10.1109/ictbig64922.2024.10911380
- Citations
- 1
- Primary Topic
- Stock Market Forecasting Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.49