Open Access iconOpen Access

ARTICLE

crossmark

A Survey on Stock Market Manipulation Detectors Using Artificial Intelligence

Mohd Asyraf Zulkifley1,*, Ali Fayyaz Munir2, Mohd Edil Abd Sukor3, Muhammad Hakimi Mohd Shafiai4

1 Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi, 43600, Malaysia
2 Faculty of Management, Virtual University of Pakistan, 54000, Lahore, Punjab, Pakistan
3 Department of Finance, Faculty of Business and Economics, Universiti Malaya, 50603, Kuala Lumpur, Malaysia
4 Center of Sustainable and Inclusive Development, Universiti Kebangsaan Malaysia, 43600, Selangor, Malaysia

* Corresponding Author: Mohd Asyraf Zulkifley. Email: email

Computers, Materials & Continua 2023, 75(2), 4395-4418. https://doi.org/10.32604/cmc.2023.036094

Abstract

A well-managed financial market of stocks, commodities, derivatives, and bonds is crucial to a country’s economic growth. It provides confidence to investors, which encourages the inflow of cash to ensure good market liquidity. However, there will always be a group of traders that aims to manipulate market pricing to negatively influence stock values in their favor. These illegal trading activities are surely prohibited according to the rules and regulations of every country’s stock market. It is the role of regulators to detect and prevent any manipulation cases in order to provide a trading platform that is fair and efficient. However, the complexity of manipulation cases has increased significantly, coupled with high trading volumes, which makes the manual observations of such cases by human operators no longer feasible. As a result, many intelligent systems have been developed by researchers all over the world to automatically detect various types of manipulation cases. Therefore, this review paper aims to comprehensively discuss the state-of-the-art methods that have been developed to detect and recognize stock market manipulation cases. It also provides a concise definition of manipulation taxonomy, including manipulation types and categories, as well as some of the output of early experimental research. In summary, this paper provides a thorough review of the automated methods for detecting stock market manipulation cases.

Keywords


Cite This Article

APA Style
Zulkifley, M.A., Munir, A.F., Sukor, M.E.A., Shafiai, M.H.M. (2023). A survey on stock market manipulation detectors using artificial intelligence. Computers, Materials & Continua, 75(2), 4395-4418. https://doi.org/10.32604/cmc.2023.036094
Vancouver Style
Zulkifley MA, Munir AF, Sukor MEA, Shafiai MHM. A survey on stock market manipulation detectors using artificial intelligence. Comput Mater Contin. 2023;75(2):4395-4418 https://doi.org/10.32604/cmc.2023.036094
IEEE Style
M.A. Zulkifley, A.F. Munir, M.E.A. Sukor, and M.H.M. Shafiai "A Survey on Stock Market Manipulation Detectors Using Artificial Intelligence," Comput. Mater. Contin., vol. 75, no. 2, pp. 4395-4418. 2023. https://doi.org/10.32604/cmc.2023.036094



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 1023

    View

  • 617

    Download

  • 0

    Like

Share Link