Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Prophecy in Financial Exchanges using ML Models

Author : Sahil Singh 1 Prashant Yadav 2 Ronit Asawa 3 Muskaan Agarwal 4 Rishu Raj 5 Surabhi K R 6

Date of Publication :6th August 2022

Abstract: Since the financial exchange is volatile and non-linear in nature, prediction is a very difficult endeavour. Machine learning and artificial neural networks have been used to perform victory in a variety of areas, as described in this paper. It's a complicated system in which a lot of people make money or lose money. This generation has been technically entered, with investors, analysts, and researchers. This paper develops a support for vector machine for financial exchange that is improved and evolved. It's a more complex and global method of conducting business. When pursuing a course of study, it is one of the most effective ways to make money. An experiment is carried out in these tasks to predict the direction of money exchange. To comprehend the future as long term, a concatenation appeal of analysis and machine language data has been constructed. The system keeps track of the stock exchange trend's perfection. This covers both fundamental and technical analysis, both of which explain the increasing and decreasing ratios in which the share and funds are calculated. This would be beneficial for newcomers and freshmen to understand the direction because it is described in straightforward terms.

Reference :

    1. Shah, D., Isah, H. and Zulkernine, F., 2019. Stock market analysis: A review and taxonomy of prediction techniques. International Journal of Financial Studies, 7(2), p.26.
    2. Bustos, O. and Pomares-Quimbaya, A., 2020. Stock market movement forecast: A Systematic Review. Expert Systems with Applications, 156, p.113464.
    3. Jose, J., Mana, S. and Samhitha, B.K., 2019. An efficient system to predict and analyze stock data using Hadoop techniques. International Journal of Recent Technology and Engineering (IJRTE), 8(2), pp.2277-3878.
    4. Hu, Z., Zhao, Y. and Khushi, M., 2021. A survey of forex and stock price prediction using deep learning. Applied System Innovation, 4(1), p.9.
    5. Obthong, M., Tantisantiwong, N., Jeamwatthanachai, W. and Wills, G., 2020. A survey on machine learning for stock price prediction: algorithms and techniques.
    6. Rouf, N.; Malik, M.B.; Arif, T.; Sharma, S.; Singh, S.; Aich, S.; Kim, H.-C. Stock Market Prediction Using Machine Learning Techniques: A Decade Survey on Methodologies, Recent Developments, and Future Directions. Electronics 2021.
    7. Krishna, V. ScienceDirect ScienceDirect NSE Stock Stock Market Market Prediction Prediction Using Using Deep-Learning Deep-Learning Models Models. Procedia Comput. Sci. 2018
    8. Srivastava, D.K. Bhambhu, L. Data classification using support vector machine. J. Theor. Appl. Inf. Technol. 2010, 12, 1–7

Recent Article